{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. 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We are looking for a Staff Software Engineer to join the Voice AI Team.\n On the Voice AI Team, our mission is to build and operate the voice platform that powers Toast and to ship novel applications on top of it that create real value across Toast's customer base. This is a greenfield space where the platform and its use cases are being defined together, and the work you do here will be foundational to how Toast uses voice AI for years to come.\n As a Staff Software Engineer on this team, you'll take ownership of significant projects end-to-end: designing systems, driving execution across the team, and making the technical decisions that shape how the platform grows. You'll work closely with product, engineering, and stakeholders across Toast to turn ambiguous problems into reliable, scalable systems.\n About this roll* (Responsibilities) \n \n Design, build, deploy, and maintain highly resilient and scalable backend services, applications, and core platform components supporting Toast's Voice AI platform used across teams\n Conceive and lead complex, cross-cutting projects from design through production, owning outcomes and driving alignment across stakeholders and across a broad range of stakeholders\n Shape the technical direction on your team and beyond by making architectural decisions, defining patterns, and reducing complexity for the engineers and teams that depend on your work\n Build and evolve integrations with AI platforms and internal Toast systems, making pragmatic tradeoffs between speed, reliability, and long-term scalability\n Establish and implement patterns for observability, monitoring, and evaluation frameworks for AI-powered systems, using production data to understand and continuously improve system behavior\n Set and hold the bar for engineering quality and best practices through standards, patterns, and written guidance that others naturally adopt, raising the bar for the team and the broader organization\n Mentor engineers at all levels through code reviews, design feedback, and technical guidance \n \n Do you have the right ingredients*? (Requirements) \n \n 8+ years of experience with object-oriented languages such as Java or Kotlin \n Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or related field\n Experience developing AI-integrated products or features , with a practical understanding of how to ship and iterate on systems that incorporate LLMs or other AI capabilities\n Experience building and reasoning about AI-powered systems , including nondeterminism, evaluation strategies, observability, and cost management\n Experience shipping complex, mission-critical production services and owning them long-term\n Track record of leading multi-person and multi-team projects end-to-end, from design through rollout\n Deep understanding of distributed systems, scalability, and production reliability\n Basic familiarity with frontend development\n Strong cross-team communication and collaboration skills; able to influence direction without formal authority both within your team and across the broader organization\n Actively uses AI coding tools (e.g., Claude Code, Cursor) in day-to-day development and have caused others to become more proficient with AI coding tools\n Experience with voice or conversational AI platforms is a plus, but not required\n \n Our Tech Stack \n Our backend services follow a microservice architecture written in Kotlin and Java using DropWizard, running on AWS (DynamoDB, RDS, Lambda). We store data in sharded Postgres databases and have our own platform for user management, canary deployments, and load balancing. Our web front-end is built with React and ES6.\n  \n AI at Toast \n At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.\n Our Total Rewards Philosophy  We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at  https://careers.toasttab.com/toast-benefits .\n  \n  \n The base salary range for this role is listed below. The starting salary will be determined","salary_min":151000,"salary_max":242000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","speech","microservices","cloud","llm"],"apply_url":"https://careers.toasttab.com/jobs?gh_jid=8131117","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-17T03:54:54Z","expires_at":"2026-09-29T13:40:06.440673Z","created_at":"2026-08-25T18:29:28.909723Z","updated_at":"2026-08-30T13:40:06.574277Z","company_name":"Toast","company_slug":"toast","company_logo_url":"https://www.google.com/s2/favicons?domain=pos.toasttab.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/23b07459-84fa-4416-bbea-feb6fb2adeba"},{"id":"dbe26e97-e089-4e96-beac-ed501c2af3e4","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Agent Experience Designer","slug":"agent-experience-designer-61d60fff","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\nAbout the Team\n\nOver the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require guidance and input throughout the development lifecycle.\n\n \n\nAbout the Role\n\nAs part of the Agent Experience Design team, you'll help shape what great AI conversation experiences look and sound like — across channels and languages, for enterprise customers around the world. You'll work directly with customers and internal teams to improve agent quality — especially in voice, one of our fastest growing channels — and build the systems and resources that allow us to scale your expertise.\n\nThis work spans research, design, enablement, and product strategy. You might:\n\n - Advise customers and internal teams on conversation design and voice selection\n\n - Evaluate and iterate on voice quality across providers, languages, and use cases\n\n - Build playbooks, rubrics, and evaluation frameworks that scale best practices across the team\n\n - Partner with Engineering and Product to translate field insights into platform improvements\n\nYour insights will shape how Decagon deploys AI in mission-critical contexts and how we build toward the next generation of intelligent systems.\n\n \n\nIn this role, you will\n\n - Design and optimize enterprise-grade AI conversation experiences across chat, voice, SMS, and email channels\n\n - Serve as a trusted advisor to customers and internal stakeholders on conversation design best practices\n\n - Evaluate voice quality and interaction patterns to maintain a high bar for naturalness and appropriateness\n\n - Build repeatable frameworks for assessing conversation and voice performance\n\n - Enable our Customer team to apply strong design judgment independently\n\n - Partner crossfunctionally with Engineering and Product to investigate quality gaps and drive improvements through clear recommendations\n\n - Share learnings and create documentation on best practices to improve consistency and raise the quality bar across deployments\n\n\n\nYour background looks something like this\n\n - 5+ years of relevant experience (e.g., voice experience design, conversation designer, product manager, applied linguistics, etc.)\n\n - Hands-on experience with voice — conversational AI, speech synthesis, or audio production\n\n - Experience migrating NLU systems to LLM and understanding key use cases for RAG functionality improvements\n\n - Experience building evaluation frameworks, rubrics, or QA processes\n\n - Strong communicator across technical and business contexts\n\n - Comfortable working close to the product in a fast-moving environment\n\n \n\nEven better if you have\n\n - Native or professional fluency in Spanish and/or familiarity with other languages\n\n - Experience with TTS providers or speech synthesis tools\n\n - Hands-on experience with frontier AI tools and deployment in enterprise or high-impact settings\n\n\n\nCompensation\n\n$180K - $220K + Offers Equity\n\n \n\n\n\nBenefits\n\nWe proudly offer the following benefits for our full-time employees:\n\n - Medical, Dental, and Vision benefits for you and your family\n\n - Life Insurance and Disability Benefits\n\n - Retirement Plan (e.g., 401K, pension)\n\n - Parental Leave\n\n - Fertility and family building benefits through Carrot\n\n - Monthly stipend to support your wellness, lifestyle, and work-life balance\n\n - Daily lunches and snacks in the office to keep you at your best\n\n - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)\n\nThese benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.","salary_min":180000,"salary_max":220000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","agents","speech","rag"],"apply_url":"https://jobs.ashbyhq.com/decagon/08b34a9e-6e98-40f3-9a81-ee6667bef97b/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-13T22:47:24.726Z","expires_at":"2026-09-29T13:37:46.1649Z","created_at":"2026-08-25T18:28:23.656624Z","updated_at":"2026-08-30T13:37:46.299319Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/dbe26e97-e089-4e96-beac-ed501c2af3e4"},{"id":"75ab7ab1-c36f-46c6-80cb-96350b135062","company_id":"37683849-8d19-405f-a4f6-9015ab2a4fed","title":"Head of Product Marketing (Toronto, Canada)","slug":"head-of-product-marketing-71a36bdb","description":"PolyAI is the Agentic Dialog Platform for building the conversational enterprise, used to build, run, govern, and improve dialog agents at scale. Powered by Raven, a proprietary dialog model trained on more than a billion enterprise conversations, PolyAI agents are built for complexity, open at every layer, and sovereign by design. PolyAI serves hundreds of enterprises across 75 languages and 25 countries, including Metro Bank, Marriott, PG\u0026E, and UniCredit. \n The Head of Product Marketing, Voice Assistants will join PolyAI’s rapidly growing marketing team. This role will own PolyAI’s core product messaging, positioning, and competitive intelligence functions. In the first few months, the person filling this position will take stock of PolyAI’s product messaging, go-to-market motions, and our key competitors. Once fully onboarded, the Head of Product Marketing, Voice Assistants will own all product messaging and be responsible for ensuring all PolyAI team members can clearly articulate our products' unique value. \n Responsibilities:  \n \n Create a product marketing strategy that enables the marketing team to consistently deliver on-brand and on-message experiences through analyst relations, content, demand generation  \n Influence our win rate through improved go-to-market strategy and enablement \n Develop resonant messaging and positioning that drives commercial outcomes for PolyAI’s world-leading voice AI products \n Catalog an understanding of PolyAI’s direct and indirect competitors and ensure that our messaging is differentiated \n Work with marketing and sales leadership to prioritize market segments and develop personas that support the content and demand generation functions \n Work with content and sales enablement team members to develop collateral that reduces friction in the sales process and increases revenue \n Build our customer understanding and market insight through customer interviews, partnerships, and industry experts  \n Support enablement initiatives across the entire revenue organization \n Create and maintain an organized and accessible database of competitive intelligence for sales, marketing, and executive leadership \n Collaborate with content team leads on thought leadership strategy and regularly contribute to the function \n Scale and lead the product marketing organization as Poly grows \n Be a capable spokesperson for the organization, both online and in-person \n \n Minimum skills and experience: \n \n 8+ years of experience in B2B tech marketing \n 3+ years of experience in a product marketing role  \n \n Preferred skills and experience: \n \n Knowledge of CCaaS, UCaaS, or Call Center technology markets \n Knowledge of NLP, NLU, or other machine-learning technology \n \n We provide a competitive salary range for this role - which is  $320,000-$420,000 OTE - depending on level and experience. Please note this range is intended as a guide, not a guarantee. Final compensation will be based on individual qualifications, relevant experience, and the scope of the role. \n \n Benefits \n 💰 Participation in the company’s employee share options plan \n 🏝 Flexible PTO policy \n 📚 Annual learning and development allowance: We will reimburse the costs of any certified and non-certified training, including conferences, events, books and subscriptions that are relevant to your role at PolyAI, in addition to any formal training that the company offers \n 🏡 We’re all about making WFH work for you - that’s why we offer a one-off WFH allowance when you join. Offering perks like noise-cancelling headphones or a comfortable desk chair to boost your comfort and focus! \n 🏥 Healthcare plan: We offer health insurance through Allianz. Full details on the plan will be shared with you on your first day \n 🌎  Sabbatical Program: 5-week paid sabbatical available after 5 years of employment \n \n At PolyAI, we take great pride in our values - they guide everything we do. We believe that a strong culture leads to meaningful work and lasting impact. \n Our core values are: \n Only the best We expect the best from our people, we hire people that expect the best from themselves, and we nurture this drive for excellence. \n Ownership We care deeply about what we do. We take ownership of our initiatives, decisions and outcomes. \n Relentlessly improve We demand more from ourselves and are always evolving. Continuous, obsessive improvement is the only way we will transform the world of conversational AI. \n Bias for action Our world moves quickly and so do we. We take calculated risks and we deliver impact fast. \n Disagree and commit We are all working toward the same goal. If we donʼt agree with something, we work hard to understand it and when a decision is made, we accept it and give it our all. \n Build for people We want the world to enjoy the experiences they have with us. We are building for a future that prefers automation. \n \n PolyAI is proud to be an equal-opportunity employer. We celebrate diver","salary_min":320000,"salary_max":420000,"location":"Canada, United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","speech","nlp","healthcare"],"apply_url":"https://job-boards.eu.greenhouse.io/polyai/jobs/4945695101","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-05T16:26:05Z","expires_at":"2026-09-29T13:38:28.341285Z","created_at":"2026-08-25T18:28:42.464898Z","updated_at":"2026-08-30T13:38:28.480523Z","company_name":"PolyAI","company_slug":"polyai","company_logo_url":"https://www.google.com/s2/favicons?domain=poly.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/75ab7ab1-c36f-46c6-80cb-96350b135062"},{"id":"caf0c303-22d7-42a7-9c71-193a58c65c8b","company_id":"6874f45d-438a-46a2-936d-735593cf0dbe","title":"Senior AI Research Engineer","slug":"senior-ai-research-engineer-459eaa2b","description":"Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!\n At Duolingo, you’ll join a team that cares about finding innovative solutions to complex technical problems , running countless experiments (300+ at a time!) with our massive user base to make data-driven decisions, and educating our users and employees alike. You’ll have limitless learning opportunities, mentorship and collaboration with world-class minds, and a variety of projects with large scopes — while doing work that’s both fun and meaningful. \n Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world.\n \n About the role... \n We are looking for a Senior AI Research Engineer to join our Duolingo Video Call team. The ideal candidate will have a proven track record as an AI research engineer, with experience across various machine learning techniques including large language models, speech models, benchmarking, and/or personalization. They will have experience at multiple levels of the ML stack, including feature engineering, developing training data, fine-tuning, reinforcement learning, quality evaluations, deployment, and monitoring. On the Video Call team, we’re building AI systems that support the core learning mission of Duolingo, improving the learning experience and helping our learners build healthy, productive habits. Given the wide array of AI domains, broad experience in AI/ML is highly desirable.\n  \n 🧠  You will... \n \n Join a full-stack team of frontend, backend and other AI Research engineers, fostering a collaborative and innovative work environment.\n Contribute to the development and training of a variety of machine learning models, including large-scale neural networks, speech recognition, and text-to-speech systems.\n Collaborate with cross-functional teams to understand their needs, to align the models’ outputs with company objectives.\n Participate in and influence strategic product and business decision making with members of the Language Learning leadership group. \n Stay up-to-date with the latest developments in machine learning and apply this knowledge to drive advancements in our projects.\n Mentor team members, providing guidance and support in their professional development.\n Ensure the delivery of high-quality, scalable, and efficient machine learning solutions.\n \n  \n ✅  You have... \n \n Proven experience as an AI research engineer, for example, in LLMs, multimodal modeling, speech, or related fields.\n Strong background in training and fine-tuning large models in an applied setting.\n Advanced degree in Computer Science, Engineering, or a related field with a focus on machine learning or artificial intelligence, or equivalent experience.\n Excellent leadership and communication skills, with the ability to lead and inspire a team.\n Technical depth sufficient to guide architecture and implementation trade‑offs, evolve quality standards, and mentor engineers on best practices.\n Deep understanding of machine learning concepts, frameworks, and best practices.\n \n The offered salary is dependent upon several factors, including work experience, skills, and internal peer comparisons. The posted range is subject to change in the future. For this role, base salary is supplemented by equity compensation. We encourage you to talk with your recruiter for more information related to compensation for this role! \n Salary Range: \n $197,200 — $266,800 USD \n Benefits: Take a peek at how we care for our employees' holistic well-being with our benefits here . Job Alerts: Sign up for job alerts here . Accommodations: We will do everything we can within reason to make sure that your interview takes place in an environment that fairly and accurately assesses your skills. If you need assistance or accommodation, please contact accommodations@duolingo.com . Equal Employment Opportunity: Duolingo is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. Fraud Warning: Unfortunately, there is a rise in scammers pretending to be real Duolingo employees. Duolingo and our employees will never ask for your Social Security number, bank details, or passport info, and we’ll never ask you to deposit a check, purchase equipment, or exchange money during the interview process. Real Duolingo employees always use an email that ends in @duolingo.com or @recruiting.duolingo.com. Stay alert and double-check these details before sharing any information. By applying for this position your data will be processed as per the Duolingo Applicant Privacy Notice ","salary_min":197200,"salary_max":266800,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["search","reinforcement-learning","fine-tuning","llm","deep-learning","speech","research","machine-learning"],"apply_url":"https://careers.duolingo.com/jobs/8656959002?gh_jid=8656959002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-29T18:34:50Z","expires_at":"2026-09-29T13:39:48.412368Z","created_at":"2026-07-30T14:09:51.119593Z","updated_at":"2026-08-30T13:39:48.547423Z","company_name":"Duolingo","company_slug":"duolingo","company_logo_url":"https://www.google.com/s2/favicons?domain=duolingo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/caf0c303-22d7-42a7-9c71-193a58c65c8b"},{"id":"6a3ecd86-aa2a-4a6f-bfc6-784fb0d4ba8b","company_id":"6874f45d-438a-46a2-936d-735593cf0dbe","title":"Senior AI Research Engineer","slug":"senior-ai-research-engineer-933388b4","description":"Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!\n At Duolingo, you’ll join a team that cares about finding innovative solutions to complex technical problems , running countless experiments (300+ at a time!) with our massive user base to make data-driven decisions, and educating our users and employees alike. You’ll have limitless learning opportunities, mentorship and collaboration with world-class minds, and a variety of projects with large scopes — while doing work that’s both fun and meaningful. \n Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world.\n \n About the role... \n We are looking for a Senior AI Research Engineer to join our Duolingo Video Call team. The ideal candidate will have a proven track record as an AI research engineer, with experience across various machine learning techniques including large language models, speech models, benchmarking, and/or personalization. They will have experience at multiple levels of the ML stack, including feature engineering, developing training data, fine-tuning, reinforcement learning, quality evaluations, deployment, and monitoring. On the Video Call team, we’re building AI systems that support the core learning mission of Duolingo, improving the learning experience and helping our learners build healthy, productive habits. Given the wide array of AI domains, broad experience in AI/ML is highly desirable.\n  \n 🧠  You will... \n \n Join a full-stack team of frontend, backend and other AI Research engineers, fostering a collaborative and innovative work environment.\n Contribute to the development and training of a variety of machine learning models, including large-scale neural networks, speech recognition, and text-to-speech systems.\n Collaborate with cross-functional teams to understand their needs, to align the models’ outputs with company objectives.\n Participate in and influence strategic product and business decision making with members of the Language Learning leadership group. \n Stay up-to-date with the latest developments in machine learning and apply this knowledge to drive advancements in our projects.\n Mentor team members, providing guidance and support in their professional development.\n Ensure the delivery of high-quality, scalable, and efficient machine learning solutions.\n \n  \n ✅  You have... \n \n Proven experience as an AI research engineer, for example, in LLMs, multimodal modeling, speech, or related fields.\n Strong background in training and fine-tuning large models in an applied setting.\n Advanced degree in Computer Science, Engineering, or a related field with a focus on machine learning or artificial intelligence, or equivalent experience.\n Excellent leadership and communication skills, with the ability to lead and inspire a team.\n Technical depth sufficient to guide architecture and implementation trade‑offs, evolve quality standards, and mentor engineers on best practices.\n Deep understanding of machine learning concepts, frameworks, and best practices.\n \n The offered salary is dependent upon several factors, including work experience, skills, and internal peer comparisons. The posted range is subject to change in the future. For this role, base salary is supplemented by equity compensation. We encourage you to talk with your recruiter for more information related to compensation for this role! \n Salary Range: \n $197,200 — $266,800 USD \n Benefits: Take a peek at how we care for our employees' holistic well-being with our benefits here . Job Alerts: Sign up for job alerts here . Accommodations: We will do everything we can within reason to make sure that your interview takes place in an environment that fairly and accurately assesses your skills. If you need assistance or accommodation, please contact accommodations@duolingo.com . Equal Employment Opportunity: Duolingo is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. Fraud Warning: Unfortunately, there is a rise in scammers pretending to be real Duolingo employees. Duolingo and our employees will never ask for your Social Security number, bank details, or passport info, and we’ll never ask you to deposit a check, purchase equipment, or exchange money during the interview process. Real Duolingo employees always use an email that ends in @duolingo.com or @recruiting.duolingo.com. Stay alert and double-check these details before sharing any information. By applying for this position your data will be processed as per the Duolingo Applicant Privacy Notice ","salary_min":197200,"salary_max":266800,"location":"Pittsburgh, PA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["speech","llm","search","deep-learning","fine-tuning","reinforcement-learning","machine-learning","research"],"apply_url":"https://careers.duolingo.com/jobs/8656931002?gh_jid=8656931002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-29T18:34:49Z","expires_at":"2026-09-29T13:39:48.507862Z","created_at":"2026-07-30T14:09:51.207702Z","updated_at":"2026-08-30T13:39:48.637838Z","company_name":"Duolingo","company_slug":"duolingo","company_logo_url":"https://www.google.com/s2/favicons?domain=duolingo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6a3ecd86-aa2a-4a6f-bfc6-784fb0d4ba8b"},{"id":"cc893f30-da8f-4b92-af53-b1e37705c3b0","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Conversation Designer","slug":"conversation-designer-8ca54f84","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\nAbout the Team\n\nOver the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require guidance and input throughout the development lifecycle.\n\n \n\nAbout the Role\n\nAs part of the Conversation Design team, you'll help shape what great AI conversation experiences look and sound like — across channels and languages, for enterprise customers around the world. You'll work directly with customers and internal teams to improve agent quality — especially in voice, one of our fastest growing channels — and build the systems and resources that allow us to scale your expertise.\n\nThis work spans research, design, enablement, and product strategy. You might:\n\n - Advise customers and internal teams on conversation design and voice selection\n\n - Evaluate and iterate on voice quality across providers, languages, and use cases\n\n - Build playbooks, rubrics, and evaluation frameworks that scale best practices across the team\n\n - Partner with Engineering and Product to translate field insights into platform improvements\n\nYour insights will shape how Decagon deploys AI in mission-critical contexts and how we build toward the next generation of intelligent systems.\n\n \n\nIn this role, you will\n\n - Design and optimize enterprise-grade AI conversation experiences across chat, voice, SMS, and email channels\n\n - Serve as a trusted advisor to customers and internal stakeholders on conversation design best practices\n\n - Evaluate voice quality and interaction patterns to maintain a high bar for naturalness and appropriateness\n\n - Build repeatable frameworks for assessing conversation and voice performance\n\n - Enable our Customer team to apply strong design judgment independently\n\n - Partner crossfunctionally with Engineering and Product to investigate quality gaps and drive improvements through clear recommendations\n\n - Share learnings and create documentation on best practices to improve consistency and raise the quality bar across deployments\n\n\n\nYour background looks something like this\n\n - 5+ years of relevant experience (e.g., voice experience design, conversation designer, product manager, applied linguistics, etc.)\n\n - Hands-on experience with voice — conversational AI, speech synthesis, or audio production\n\n - Experience migrating NLU systems to LLM and understanding key use cases for RAG functionality improvements\n\n - Experience building evaluation frameworks, rubrics, or QA processes\n\n - Strong communicator across technical and business contexts\n\n - Comfortable working close to the product in a fast-moving environment\n\n \n\nEven better if you have\n\n - Native or professional fluency in Spanish and/or familiarity with other languages\n\n - Experience with TTS providers or speech synthesis tools\n\n - Hands-on experience with frontier AI tools and deployment in enterprise or high-impact settings\n\n\n\nCompensation\n\n$180K - $220K + Offers Equity\n\n \n\n\n\nBenefits\n\nWe proudly offer the following benefits for our full-time employees:\n\n - Medical, Dental, and Vision benefits for you and your family\n\n - Life Insurance and Disability Benefits\n\n - Retirement Plan (e.g., 401K, pension)\n\n - Parental Leave\n\n - Fertility and family building benefits through Carrot\n\n - Monthly stipend to support your wellness, lifestyle, and work-life balance\n\n - Daily lunches and snacks in the office to keep you at your best\n\n - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)\n\nThese benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.","salary_min":180000,"salary_max":220000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","agents","rag","speech"],"apply_url":"https://jobs.ashbyhq.com/decagon/ad6db669-0ff9-41c6-b86b-8e567ad7fbbd/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-22T18:54:26.948Z","expires_at":"2026-09-29T13:37:45.418451Z","created_at":"2026-08-25T18:28:23.618593Z","updated_at":"2026-08-30T13:37:45.552613Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/cc893f30-da8f-4b92-af53-b1e37705c3b0"},{"id":"0003f63a-b2b2-44e0-b588-7a3de39a2516","company_id":"28040a6c-6f94-41a4-b15a-f2e4520188ff","title":"Voice Experience Designer, Agentic Voice","slug":"agent-experience-designer-agentic-voice-00a4cb3f","description":"About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. \n Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. \n Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. \n Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. \n We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. \n We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . \n Your role As a Voice Experience ( VX ) Designer, you'll own the voices, personalities, and interactions that make an AI agent feel intuitive, empathetic, and human. We're going all-in on agentic AI under one core idea: stop answering, start resolving. A voice agent that resolves is only as good as the experience it delivers; designing that entire voice experience is your job. \n Reporting directly to the VP of AI Products, you'll define the personas, standards, and quality bar that our Speech engineering team implements and that forward-deployed VX designers apply account-by-account in the field. You author the voice; they build the machine that renders it, and the field applies it. You'll collaborate hand-in-hand with our AI engineers to shape model judgment through prompts and flow orchestration rather than hard-coded branches. \n You'll bring a deep sense of behavioral and emotional design to the platform, ensuring our agents have the taste, pacing, and vocabulary to sound truly competent and empathetic across both happy paths and high-stakes moments. \n This position has the opportunity to be based in our Bay Area office. \n What you’ll do \n \n Own the persona: Define the agent's global voice, character, and personality, and maintain persona consistency across every vertical we ship. \n Set the voice palette \u0026 house standards: Establish the standards for pacing, prosody, and emphasis that Speech engineering implements and forward-deployed teams apply to build brand-specific experiences. \n Define the quality bar: Own the universal platform quality bar — Consistency, Fluency, perceived Latency and acceptable trade-offs — and tie persona decisions directly to core metrics like resolution, containment, and sentiment. \n Design behavior with prompts: Partner with AI engineers to orchestrate escalation instincts, confirmation patterns, and graceful recovery using advanced prompting rather than rigid dialogue trees — expressing design intent that alters model outputs without writing code. \n Own handoff \u0026 turn-taking experience: Design standard handoff patterns where context is fully preserved when an agent passes a caller to a human, and shape turn-taking and barge-in behavior in partnership with the Speech team. \n Design for emotional states: Research and design for distinct behavioral and emotional user states — a patient disputing a bill, a dispatcher tracing a late delivery — so the agent adapts seamlessly across happy paths and high-stakes moments. \n \n Skills you’ll bring \n \n Experience: 5+ years shaping voice user interfaces (VUI), character writing, conversation design, or complex conversational/agentic systems. \n Education: Bachelor's in Linguistics, Communication, Psychology, Design, or equivalent practical experience. \n Prompt fluency: Fluency with LLM-based agent behaviors, prompt engineering, and prompt orchestration — knowing how design choices alter model outputs without relying on code. \n TTS literacy: Working fluency with TTS controls (voice selection, prosodic control) sufficient to set platform standards — the Speech team implements them. \n Portfolio: An exceptional portfolio highlighting voice systems, written persona standards, and interactive logic rather than static flow diagrams. \n Taste: Strong taste and an ear for dia","salary_min":179000,"salary_max":227000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["speech","llm","fine-tuning","agents","healthcare"],"apply_url":"https://job-boards.greenhouse.io/dialpad/jobs/8633475002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T20:04:06Z","expires_at":"2026-09-29T13:50:50.748581Z","created_at":"2026-07-15T14:23:00.567276Z","updated_at":"2026-08-30T13:50:50.878143Z","company_name":"Dialpad","company_slug":"dialpad","company_logo_url":"https://www.google.com/s2/favicons?domain=dialpad.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0003f63a-b2b2-44e0-b588-7a3de39a2516"},{"id":"dc54d254-d290-4242-871b-1d784c72c570","company_id":"0fc88a91-688e-421d-917d-4880569dd976","title":"Principal Research \u0026 Engineering, Realtime Voice AI","slug":"principal-research-engineering-realtime-voice-ai-9c626749","description":"About Inflection AI \n Inflection AI is a Public Benefit Corporation empowering people with human-centered, emotionally intelligent AI. We’re shaping the future of AI by combining emotional intelligence (EQ) and raw intelligence (IQ) to elevate people’s potential. Inflection AI created Pi, the world’s first emotionally intelligent AI, to help people work through decisions, emotions, and challenges. Pi is a personal AI agent powered by Inflection AI’s foundation model, proving that AI can be personal, empathetic, and contextually aware.\n About the Role \n Voice is becoming the highest-stakes interface for AI, where quality depends on speed, naturalness, interruption handling, emotional nuance, and reliability in real-world conditions. We are looking for a hands-on technical leader to define and build Inflection’s realtime Voice AI stack across speech models, streaming systems, voice-agent runtime, and evaluation. This person will help shape how emotionally intelligent AI shows up in spoken interactions, partnering across research, engineering, product, and design to deliver voice agents that feel responsive, trustworthy, and useful in enterprise settings. \n What You’ll Do \n \n Establish the technical roadmap for Inflection's realtime Voice AI stack, encompassing streaming ASR, TTS, speech-to-speech, speech LLMs, turn-taking, barge-in, latency, and reliability.\n Utilize a 1,000 GPU cluster to support performance benchmarking and extensive experimentation.\n Determine build-vs-buy-vs-train strategies for core audio, speech, and realtime interaction components.\n Direct research and engineering efforts focused on speech quality, naturalness, expressiveness, emotional fit, controllability, and production readiness.\n Collaborate with infrastructure, product, design, and agentic AI teams to deploy voice agents for enterprise workflows.\n Develop evaluation systems measuring voice quality through metrics such as clarity, emotional appropriateness, interruption handling, task success, user preference, latency, and reliability, moving beyond standard WER.\n Refine production voice behavior by debugging across runtime, model, evaluation, data, and product layers.\n Mentor, and Coach a team specializing in speech research, audio infrastructure, realtime systems, and evaluation.\n \n What We’re Looking For \n \n Experience leading or serving as a principal Research and Engineering contributor to realtime voice, speech, audio AI, or conversational AI systems in production.\n Experience with one or more of: streaming ASR, TTS, speech-to-speech systems, speech LLMs, audio tokenization, multimodal models, barge-in, low-latency inference, or realtime agents.\n Strong technical judgment across both speech modeling and production systems.\n Ability to define voice quality in terms of user and customer outcomes, not only offline model metrics.\n Experience designing or using evaluation systems that capture real user experience.\n Strong product intuition for natural, trustworthy, emotionally appropriate voice interactions.\n Ability to lead senior technical talent while staying close to the code, architecture, and debugging work.\n Have a bachelor’s degree or equivalent in a related field to the offered position requirements\n \n Employee Pay Disclosures \n At Inflection AI, we aim to attract and retain the best employees and compensate them in a way that appropriately and fairly values their individual contributions to the company. For this role, Inflection AI estimates a starting annual base salary to fall within the range of $400,000 to $550,000 , depending on a candidate’s qualifications and level of experience. This role also includes a meaningful equity component, allowing employees to share in the long-term success of the company.\n  \n Benefits \n Inflection AI values and supports our team’s mental, emotional, financial and physical health. We are focused on building a positive, safe, inclusive and inspiring place to work. Our benefits include: \n \n Robust medical, dental and vision options with employer contributions for HSA, FSA and DFSA\n 401k matching program \n Flexible Time Off, 10 paid holidays, 5 days sick leave\n Parental, Medical and Family care leave \n Generous cell-phone, wellness and office set up stipends \n Support of country-specific visa needs for international employees living in the Bay Area","salary_min":400000,"salary_max":550000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["speech","gpu","generative-ai","agents","llm","research"],"apply_url":"https://boards.greenhouse.io/inflectionai/jobs/4693024006?gh_jid=4693024006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-29T18:24:22Z","expires_at":"2026-09-29T13:35:18.114029Z","created_at":"2026-06-30T14:04:31.512807Z","updated_at":"2026-08-30T13:35:18.249518Z","company_name":"Inflection AI","company_slug":"inflection-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=inflection.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/dc54d254-d290-4242-871b-1d784c72c570"},{"id":"b17f9ab1-1081-41a6-88dd-ae290d7d1c94","company_id":"28040a6c-6f94-41a4-b15a-f2e4520188ff","title":"AI Engineer, Agentic Voice (TTS)","slug":"ai-engineer-voice-designer-9541704c","description":"About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. \n Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. \n Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. \n Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. \n We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. \n We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . \n Your role As an AI Engineer on our Speech Team, you'll own the back-end implementation and linguistic optimization of the voice ( TTS ) layer for our next-generation AI agents. You'll work squarely within our Speech Team, a high-impact R\u0026D and engineering group focused on speech recognition, enhancement, and synthesis; bridging core speech science and product engineering so our agents sound human, context-aware, and trustworthy. \n You’ll build the systems that render voice: integrating and optimizing TTS engines, engineering the persona and parameter machinery, and exposing voice attributes to our customer-facing UI. You'll partner closely with our Voice Experience Designer, who authors and owns the persona standards and quality bar that you implement — you own the platform that makes their designs real, fast, and consistent at scale. \n This position reports to our Senior Manager, AI Speech, is based at our Kitchener hub, and operates on a hybrid schedule. \n What you’ll do \n \n TTS backend implementation: Own the integration and optimization of multiple TTS vendor APIs behind a unified interface with failover, and lead research and prototyping of open-source and in-house TTS architectures. \n Latency \u0026 pipeline engineering: Minimize time-to-first-audio and end-to-end latency across the ASR → LLM → TTS pipeline while maintaining or optimizing voice quality, in partnership with ASR and Audio AI engineers. \n Linguistic optimization: Apply your knowledge of phonetics and sociolinguistics to format TTS input for maximum naturalness — SSML tags, punctuation-driven prosody, and text normalization for names, numbers, dates, and currency. \n Persona system \u0026 parameter exposure: Build the persona parameterization system and architect the logic that exposes voice attributes to the product UI, implementing the house standards defined by Agent Experience Design. \n Prompt engineering as code: Manage structured LLM and TTS prompt templates with versioning and a rigorous evaluation harness. \n Conversational turn design: Engineer context- and state-aware \"thinking\" utterances that maintain caller trust while tool calls and model steps run under the hood. \n \n Skills you’ll bring \n \n Technical foundation: Strong Python and hands-on experience with deep learning frameworks (e.g. PyTorch). \n Speech expertise: 3+ years in Speech Synthesis ( TTS ) or applied speech ML, including hands-on work with frameworks like NVIDIA NeMo, ESPnet, or Coqui, and with major TTS APIs such as ElevenLabs, Rime, and Cartesia. \n Linguistic background: Degree in Computational Linguistics, Computer Science, or AI/ML, with a strong understanding of phonetics, prosody, and syntax you can apply in code ( G2P , pronunciation dictionaries, text normalization). \n Backend engineering: Experience building production-grade APIs and integrating multi-vendor services in a cloud environment (GCP preferred). \n Evaluation mindset: Fluency with speech-quality metrics (MOS, intelligibility, latency) and the ability to design and execute rigorous A/B tests for voice personas. \n Prompt engineering: Proven experience crafting, versioning, and evaluating LLM prompts (system, few-shot) and structured templates. \n \n This is a builder role in a science/infrastructure org. If your strength is conversation d","salary_min":145000,"salary_max":172500,"location":"Kitchener, Canada","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["llm","agents","fine-tuning","cloud","speech","deep-learning","pytorch"],"apply_url":"https://job-boards.greenhouse.io/dialpad/jobs/8601273002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-19T17:07:59Z","expires_at":"2026-09-29T13:50:48.728439Z","created_at":"2026-06-28T14:19:26.870692Z","updated_at":"2026-08-30T13:50:48.858327Z","company_name":"Dialpad","company_slug":"dialpad","company_logo_url":"https://www.google.com/s2/favicons?domain=dialpad.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b17f9ab1-1081-41a6-88dd-ae290d7d1c94"},{"id":"7eb3a4f0-b9e4-4d32-8d4b-045ffe5c6ed8","company_id":"28040a6c-6f94-41a4-b15a-f2e4520188ff","title":"AI Engineer, Agentic Voice (TTS)","slug":"ai-engineer-voice-designer-c02cea46","description":"About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. \n Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. \n Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. \n Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. \n We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. \n We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . \n Your Role As an AI Engineer on our Speech Team, you'll own the back-end implementation and linguistic optimization of the voice ( TTS ) layer for our next-generation AI agents. You'll work squarely within our Speech Team, a high-impact R\u0026D and engineering group focused on speech recognition, enhancement, and synthesis; bridging core speech science and product engineering so our agents sound human, context-aware, and trustworthy. \n You’ll build the systems that render voice: integrating and optimizing TTS engines, engineering the persona and parameter machinery, and exposing voice attributes to our customer-facing UI. You'll partner closely with our Voice Experience Designer, who authors and owns the persona standards and quality bar that you implement — you own the platform that makes their designs real, fast, and consistent at scale. \n This position reports to our Sr. Manager, AI Speech, is based at our Vancouver hub, and operates on a hybrid schedule. \n What you’ll do \n \n TTS backend implementation: Own the integration and optimization of multiple TTS vendor APIs behind a unified interface with failover, and lead research and prototyping of open-source and in-house TTS architectures. \n Latency \u0026 pipeline engineering: Minimize time-to-first-audio and end-to-end latency across the ASR → LLM → TTS pipeline while maintaining or optimizing voice quality, in partnership with ASR and Audio AI engineers. \n Linguistic optimization: Apply your knowledge of phonetics and sociolinguistics to format TTS input for maximum naturalness — SSML tags, punctuation-driven prosody, and text normalization for names, numbers, dates, and currency. \n Persona system \u0026 parameter exposure: Build the persona parameterization system and architect the logic that exposes voice attributes to the product UI, implementing the house standards defined by Agent Experience Design. \n Prompt engineering as code: Manage structured LLM and TTS prompt templates with versioning and a rigorous evaluation harness. \n Conversational turn design: Engineer context- and state-aware \"thinking\" utterances that maintain caller trust while tool calls and model steps run under the hood. \n \n Skills you’ll bring \n \n Technical foundation: Strong Python and hands-on experience with deep learning frameworks (e.g. PyTorch). \n Speech expertise: 3+ years in Speech Synthesis ( TTS ) or applied speech ML, including hands-on work with frameworks like NVIDIA NeMo, ESPnet, or Coqui, and with major TTS APIs such as ElevenLabs, Rime, and Cartesia. \n Linguistic background: Degree in Computational Linguistics, Computer Science, or AI/ML, with a strong understanding of phonetics, prosody, and syntax you can apply in code ( G2P , pronunciation dictionaries, text normalization). \n Backend engineering: Experience building production-grade APIs and integrating multi-vendor services in a cloud environment (GCP preferred). \n Evaluation mindset: Fluency with speech-quality metrics (MOS, intelligibility, latency) and the ability to design and execute rigorous A/B tests for voice personas. \n Prompt engineering: Proven experience crafting, versioning, and evaluating LLM prompts (system, few-shot) and structured templates. \n \n This is a builder role in a science/infrastructure org. If your strength is conversation desi","salary_min":161500,"salary_max":191500,"location":"Vancouver, Canada","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["cloud","fine-tuning","pytorch","agents","speech","deep-learning","llm"],"apply_url":"https://job-boards.greenhouse.io/dialpad/jobs/8597852002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-19T17:04:22Z","expires_at":"2026-09-29T13:50:48.63335Z","created_at":"2026-06-28T14:19:26.794215Z","updated_at":"2026-08-30T13:50:48.762932Z","company_name":"Dialpad","company_slug":"dialpad","company_logo_url":"https://www.google.com/s2/favicons?domain=dialpad.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7eb3a4f0-b9e4-4d32-8d4b-045ffe5c6ed8"},{"id":"bc38cbd7-6147-49eb-a610-64fb031af669","company_id":"6ea0f41a-b13e-481a-b410-5195f391f939","title":"Staff Machine Learning Engineer, Voice AI ","slug":"staff-machine-learning-engineer-voice-ai-049973bf","description":"About the Role \n Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability.\n We're looking for a Staff ML Engineer to drive the model serving layer for voice workloads. You'll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro — pushing latency and throughput to the frontier. You'll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly.\n This is a foundational hire on a small, high-impact team. Voice inference has unique challenges — streaming audio, tokenization, real-time latency budgets — that require dedicated ML engineering focus. You'll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech.\n \n Own the model serving stack that powers Together's voice platform across STT, TTS, and speech-to-speech.\n Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference.\n Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together's infrastructure.\n Build quality evaluation frameworks that guide model selection for customers and inform the roadmap.\n Join a small, early-stage team with outsized impact on a fast-growing product area.\n \n  \n Responsibilities \n \n Own the voice inference roadmap end-to-end — define and execute the technical strategy for optimizing STT, TTS, and speech-to-speech models across Together's infrastructure, with a clear-eyed view of where the field is heading and how to position the platform ahead of it.\n Drive best-in-class inference performance — architect and implement systems targeting leading TTFB, throughput, and GPU utilization for voice workloads; set the performance bar others in the industry measure against, not just catch up to.\n Lead productionization of voice models at scale — design the serving architecture for serverless and dedicated endpoints, including batching strategies, streaming inference pipelines, and memory management tailored to real-time audio; own reliability and latency SLAs.\n Build the voice evaluation platform — design a rigorous, extensible evaluation framework covering WER across accents, languages, and noise conditions for STT; naturalness, latency, and pronunciation fidelity for TTS; establish the internal benchmark methodology that informs model selection and roadmap decisions.\n Shape the architecture for next-generation model support — anticipate and enable emerging model paradigms — audio-native LLMs, codec-based architectures (SNAC, Encodec), and end-to-end speech-to-speech systems — before they're mainstream, not after.\n Serve as the technical DRI for model partner integrations — lead deep collaboration with partners such as Cartesia, Deepgram, and Rime; own the full lifecycle from integration to optimization to ongoing performance accountability.\n Diagnose and resolve the hardest performance problems in the stack — conduct systematic profiling and root-cause analysis from GPU kernel behavior to framework-level bottlenecks; drive shipped improvements with documented, measurable impact.\n Influence platform architecture across the organization — partner with platform engineering leadership to ensure the serving layer is built for the latency and reliability demands of real-time voice APIs; your technical decisions should raise the ceiling for the whole team.\n Define and scale voice fine-tuning capabilities — lead the technical direction for enabling customers to fine-tune STT and TTS models on Together's infrastructure, establishing the primitives for differentiated voice experiences.\n Lay technical foundations for a category-defining product surface — architect systems with enough foresight that they support multiple new voice products with minimal rework; think in terms of platforms, not point solutions.\n \n Requirements \n \n 8+ years of ML engineering experience, with a demonstrated focus on model serving, inference optimization, or ML infrastructure at production scale — including systems you've owned from design through live traffic.\n Deep, practical expertise in LLM serving engines (vLLM, SGLang, TensorRT-LLM, or equivalent) — you've modified engine internals, debugged edge cases under load, and contributed improvements back; you don't stop at the API surface.\n Expert-level Python and PyTorch proficiency, with a strong command of GPU optimization — CUDA kernels, memory hierarchies, profiling toolchains — and a track record of turning that knowledge into shipped latency or throughput wins.\n Proven system design judgment — you've made arch","salary_min":220000,"salary_max":280000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["gpu","mlops","pytorch","speech","fine-tuning","llm","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/togetherai/jobs/5140763007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-19T18:19:46Z","expires_at":"2026-09-29T13:32:22.809857Z","created_at":"2026-05-27T14:02:00.695384Z","updated_at":"2026-08-30T13:32:22.950612Z","company_name":"Together AI","company_slug":"together-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=together.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/bc38cbd7-6147-49eb-a610-64fb031af669"},{"id":"e166cabe-5ba5-4fe5-a30d-688ddd5f8fc1","company_id":"5dfcd8fc-f8dd-4f46-b613-ca6da467ff4b","title":"Machine Learning Researcher, Audio","slug":"machine-learning-researcher-audio-6b0906fa","description":"MACHINE LEARNING RESEARCHER, AUDIO\n\nLocation: San Francisco, CA or Remote\n\n \n \n\n\nABOUT BLAND\n\nAt Bland.com, our mission is to empower enterprises to build AI phone agents at scale. Based in San Francisco, we are a fast-growing team reimagining how customers interact with businesses through voice. We have raised $100 million from leading Silicon Valley investors, including Emergence Capital, Scale Venture Partners, Y Combinator, and founders of Twilio, Affirm, and ElevenLabs.\n\n \n\nVoice is quickly becoming the primary interface between businesses and their customers. We are building the models and infrastructure that make those interactions feel natural, reliable, and genuinely human.\n\n \n \n\n\nTHE ROLE: MACHINE LEARNING RESEARCHER, AUDIO\n\nAs a Machine Learning Researcher at Bland, you'll be working on foundational research and development across the core components of our voice stack: speech-to-text, large language models, neural audio codecs, and text-to-speech. Your work will define how our agents understand, reason, and speak in real time at enterprise scale.\n\n \n\nThis is not a narrow research role. You will take ideas from theory to large-scale training to production inference systems serving millions of calls per day. You will design new modeling approaches, validate them with rigorous experimentation, and collaborate with engineering teams to deploy them into real customer environments.\n\n \n \n\n\nWHAT YOU WILL DO\n\nBuild and Scale Next-Generation TTS Systems\n\n - Design and train large scale text-to-speech models capable of expressive, controllable, human-sounding output.\n\n - Develop neural audio codec-based TTS architectures for efficient, high-fidelity generation.\n\n - Improve prosody modeling, question inflection, emotional expression, and multi-speaker robustness.\n\n - Optimize for real-time, low-latency inference in production.\n\n \n\nAdvance Speech-to-Text Modeling\n\n - Build and fine-tune large scale ASR systems robust to accents, noise, telephony artifacts, and code switching.\n\n - Leverage self-supervised pretraining and large-scale weak supervision.\n\n - Improve transcription accuracy for real-world enterprise scenarios, including structured extraction and conversational nuance.\n\n \n\nPioneer Neural Audio Codecs\n\n - Research and implement neural audio codecs that achieve extreme compression with minimal perceptual loss.\n\n - Explore discrete and continuous latent representations for scalable speech modeling.\n\n - Design codec architectures that enable downstream generative modeling and controllable synthesis.\n\n \n\nDevelop Scalable Training Pipelines\n\n - Curate and process massive audio datasets across languages, speakers, and environments.\n\n - Design staged training curricula and data filtering strategies.\n\n - Scale training across distributed GPU clusters focusing on cost, throughput, and reliability.\n\n \n\nRun Rigorous Experiments\n\n - Design ablation studies that isolate the impact of architectural changes.\n\n - Measure improvements using both objective metrics and perceptual evaluations.\n\n - Validate ideas quickly through focused experiments that confirm or eliminate hypotheses.\n\n \n \n\n\nWHAT MAKES YOU A GREAT FIT\n\nDeep Research Foundations\n\n - Experience with self-supervised learning, multimodal modeling, or generative modeling.\n\n - Ability to derive new formulations and implement them efficiently.\n\n \n\nExpertise in Voice Modeling\n\n - Hands-on experience building or scaling TTS, STT, or neural audio codec systems.\n\n - Familiarity with large scale speech datasets and real-world audio variability.\n\n - Strong intuition for audio quality, prosody, and conversational dynamics.\n\n \n\nSystems and Hardware Awareness\n\n - Experience training and serving large models on modern accelerators.\n\n - Knowledge of inference optimization techniques, including quantization, kernel optimization, and memory efficiency.\n\n - Understanding of real-time constraints in telephony or streaming environments.\n\n \n\nExperimental Rigor\n\n - Track record of designing controlled experiments and meaningful ablations.\n\n - Comfortable working with both offline benchmarks and live production metrics.\n\n - Ability to move quickly from hypothesis to validation.\n\n \n\nBuilder Mentality\n\n - Comfortable in fast-moving startup environments.\n\n - Strong ownership mindset from research through deployment.\n\n - Excited by ambiguous, unsolved problems.\n\n \n \n\n\nHOW YOU SHOW UP\n\n - You treat unsolved problems as opportunities to invent new paradigms.\n\n - You identify the single experiment that can validate an idea in days, not months.\n\n - You measure everything and let data drive decisions.\n\n - You are obsessed with making voice agents sound truly human.\n\n - You use AI tools aggressively to amplify your own impact and accelerate research cycles.\n\n \n \n\n\nBONUS POINTS\n\n - Experience with large scale distributed training.\n\n - Research publications or open source contributions in speech or language AI.\n\n - Background in real-time speech systems or telephony.\n\n","salary_min":160000,"salary_max":250000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pre-training","healthcare","llm","gpu","speech","distributed-systems","machine-learning","research"],"apply_url":"https://jobs.ashbyhq.com/bland/2e815d0d-8e7a-43cc-8853-c1b029aeb499/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-04-20T22:07:11.702Z","expires_at":"2026-09-29T13:36:46.398392Z","created_at":"2026-04-22T15:40:14.708917Z","updated_at":"2026-08-30T13:36:46.538324Z","company_name":"Bland AI","company_slug":"bland-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=bland.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e166cabe-5ba5-4fe5-a30d-688ddd5f8fc1"},{"id":"92e0e6b0-3459-44ec-9e1a-4e36a7b805d4","company_id":"4d985fa4-b897-4f93-9745-c332367ad86b","title":"Research Scientist - LLM ","slug":"research-scientist-llm-80f40837","description":"ABOUT RETELL AI\n\nRetell AI is using first-principles thinking to reimagine the call center with cutting-edge voice AI. Thousands of companies now use Retell's AI voice agents to handle sales, support, and logistics calls that once required large teams of human agents. Backed by Y Combinator, Alt Capital, and other leading investors, we've scaled to $80M in ARR with a team of 50, up from $5M at the start of 2025, and are now valued at over $1.5B.\n\nOur vision for 2026 is to build a modern CX platform where entire contact centers are powered by AI. Instead of basic automation that needs constant human tuning, we're creating intelligent AI “workers” that act as frontline agents, QA analysts, and managers, continuously executing, monitoring, and improving every customer interaction.\n\nWe're growing fast and looking for ambitious builders who want to tackle hard technical problems, move quickly, and have a real impact on one of the fastest-growing voice AI companies in the world.\n\nLet's build the future together.\n\nRecent recognition:\n\n - No. 1 Best Places to Work in the Bay Area, San Francisco Business Times 2026 https://finance.yahoo.com/technology/ai/articles/voice-ai-startup-retell-ai-145200025.html\n\n - Top 50 AI Apps, a16z (2025) https://a16z.com/the-ai-application-spending-report-where-startup-dollars-really-go/\n\n - #3 Fastest-Growing Software Company, G2 Best Software Awards 2026 https://company.g2.com/news/g2s-2026-best-software-awards\n\n - Best Agentic AI Software, G2 Best Software Awards 2026 https://www.retellai.com/blog/retell-ai-recognized-as-the-best-agentic-ai-software-by-g2\n\n - #4 Fastest-Growing Software Vendor, Brex Benchmark 2025 https://www.brex.com/journal/brex-benchmark-december-2025\n\n - Enterprise Tech 30 Class of 2026, Nasdaq \u0026 Wing VC https://www.nasdaq.com/videos/retell-ai\n\n - Top-Ranked Startup, Lean AI Leaderboard https://leanaileaderboard.com/\n\n - Backed by Y Combinator https://www.ycombinator.com/companies/retell-ai\n\n \n\n\nABOUT THE ROLE\n\nRetell AI transforms customer experience with voice AI for enterprises, including customers like CVS/Aetna, American Airlines, Lenovo, and Grab. We have more customer stories than we can tell!\n\nThis is a research-driven, high-impact role for ML researchers who want to push the boundaries of real-time AI. As a Founding Machine Learning Research Engineer at Retell, you’ll focus on advancing model capabilities for human-like voice agents operating in complex, real-world environments.\n\nYou’ll explore new approaches across LLMs and audio models, design novel evaluation methods, and prototype systems that improve reasoning, latency, and conversational quality. Your work will directly influence production systems, bridging cutting-edge research with real-world deployment.\n\nIf you’re excited about solving open-ended ML problems, experimenting rapidly, and shaping how voice AI systems think and perform, this is a unique opportunity to do so at scale.\n\n\n\n\nKEY RESPONSIBILITIES\n\n - Research \u0026 Experimentation – Explore and develop new techniques across LLMs and audio models to improve reasoning, latency, and conversational quality in real-time systems.\n\n - Model Training – Rapidly build and iterate on models and pipelines, turning research ideas into working prototypes. Innovate on paradigms, training methods, and inference.\n\n - Evaluation \u0026 Benchmarking – Design novel evaluation frameworks, datasets, and metrics to measure performance on complex, real-world voice tasks.\n\n - Bridge Research to Production – Collaborate closely with engineering to translate research insights into deployable systems.\n\n - Human Feedback Loops – Develop methods to incorporate human evaluation into model improvement, especially for subjective conversational quality.\n\n - Advance the Frontier – Stay at the cutting edge of ML research and bring new ideas into Retell’s product and infrastructure.\n\n\n\n\nREQUIRED\n\n - Strong ML Research Background – You've worked on advanced ML problems (like LLM pre-training and post-training, transcription model training, TTS, or multimodal systems), either in industry or academia.\n\n - Deep Technical Foundation – Comfortable with PyTorch, model architectures, and the math behind modern machine learning.\n\n - Top Academic Background – Master's degree in CS, ML, AI or related field required; PhD preferred. Equivalent research-level engineering experience also considered.\n\n\n\n\nYOU MIGHT THRIVE IF YOU\n\n - Published or Awarded – First/co-author publications at top-tier venues (NeurIPS, ICML, ICLR, ACL, Interspeech, etc.) or notable competition awards are a strong plus.\n\n - Experimental Mindset – You enjoy exploring open-ended problems and iterating quickly on ideas.\n\n - Bridge Theory \u0026 Practice – You can translate research into systems that work in real-world environments.\n\n - Startup-Ready – You thrive in fast-paced environments with high ownership and ambiguity.\n\n - Collaborative \u0026 Clear Communicator – You can explain complex i","salary_min":225000,"salary_max":400000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","pytorch","search","pre-training","speech","agents","research"],"apply_url":"https://jobs.ashbyhq.com/retell-ai/b0d780eb-df25-49d0-859a-915de204a2f2/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-04-14T05:52:56.477Z","expires_at":"2026-09-29T13:41:58.877846Z","created_at":"2026-04-16T11:17:45.913083Z","updated_at":"2026-08-30T13:41:59.012228Z","company_name":"Retell AI","company_slug":"retell-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=retellai.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/92e0e6b0-3459-44ec-9e1a-4e36a7b805d4"},{"id":"acc5d396-6aa2-40ba-8a49-632774606bde","company_id":"4d985fa4-b897-4f93-9745-c332367ad86b","title":"Research Scientist - Audio ","slug":"research-scientist-audio-918408c6","description":"ABOUT RETELL AI\n\nRetell AI is using first-principles thinking to reimagine the call center with cutting-edge voice AI. Thousands of companies now use Retell's AI voice agents to handle sales, support, and logistics calls that once required large teams of human agents. Backed by Y Combinator, Alt Capital, and other leading investors, we've scaled to $80M in ARR with a team of 50, up from $5M at the start of 2025, and are now valued at over $1.5B.\n\nOur vision for 2026 is to build a modern CX platform where entire contact centers are powered by AI. Instead of basic automation that needs constant human tuning, we're creating intelligent AI “workers” that act as frontline agents, QA analysts, and managers, continuously executing, monitoring, and improving every customer interaction.\n\nWe're growing fast and looking for ambitious builders who want to tackle hard technical problems, move quickly, and have a real impact on one of the fastest-growing voice AI companies in the world.\n\nLet's build the future together.\n\nRecent recognition:\n\n - No. 1 Best Places to Work in the Bay Area, San Francisco Business Times 2026 https://finance.yahoo.com/technology/ai/articles/voice-ai-startup-retell-ai-145200025.html\n\n - Top 50 AI Apps, a16z (2025) https://a16z.com/the-ai-application-spending-report-where-startup-dollars-really-go/\n\n - #3 Fastest-Growing Software Company, G2 Best Software Awards 2026 https://company.g2.com/news/g2s-2026-best-software-awards\n\n - Best Agentic AI Software, G2 Best Software Awards 2026 https://www.retellai.com/blog/retell-ai-recognized-as-the-best-agentic-ai-software-by-g2\n\n - #4 Fastest-Growing Software Vendor, Brex Benchmark 2025 https://www.brex.com/journal/brex-benchmark-december-2025\n\n - Enterprise Tech 30 Class of 2026, Nasdaq \u0026 Wing VC https://www.nasdaq.com/videos/retell-ai\n\n - Top-Ranked Startup, Lean AI Leaderboard https://leanaileaderboard.com/\n\n - Backed by Y Combinator https://www.ycombinator.com/companies/retell-ai\n\n \n\n\nABOUT THE ROLE\n\nRetell AI transforms customer experience with voice AI for enterprises, including customers like CVS/Aetna, American Airlines, Lenovo, and Grab. We have more customer stories than we can tell!\n\nThis is a research-driven, high-impact role for ML researchers who want to push the boundaries of real-time AI. As a Founding Machine Learning Research Engineer at Retell, you’ll focus on advancing model capabilities for human-like voice agents operating in complex, real-world environments.\n\nYou’ll explore new approaches across LLMs and audio models, design novel evaluation methods, and prototype systems that improve reasoning, latency, and conversational quality. Your work will directly influence production systems, bridging cutting-edge research with real-world deployment.\n\nIf you’re excited about solving open-ended ML problems, experimenting rapidly, and shaping how voice AI systems think and perform, this is a unique opportunity to do so at scale.\n\n\n\n\nKEY RESPONSIBILITIES\n\n - Research \u0026 Experimentation – Explore and develop new techniques across LLMs and audio models to improve reasoning, latency, and conversational quality in real-time systems.\n\n - Model Training – Rapidly build and iterate on models and pipelines, turning research ideas into working prototypes. Innovate on paradigms, training methods, and inference.\n\n - Evaluation \u0026 Benchmarking – Design novel evaluation frameworks, datasets, and metrics to measure performance on complex, real-world voice tasks.\n\n - Bridge Research to Production – Collaborate closely with engineering to translate research insights into deployable systems.\n\n - Human Feedback Loops – Develop methods to incorporate human evaluation into model improvement, especially for subjective conversational quality.\n\n - Advance the Frontier – Stay at the cutting edge of ML research and bring new ideas into Retell’s product and infrastructure.\n\n\n\n\nREQUIRED\n\n - Strong ML Research Background – You've worked on advanced ML problems (like LLM pre-training and post-training, transcription model training, TTS, or multimodal systems), either in industry or academia.\n\n - Deep Technical Foundation – Comfortable with PyTorch, model architectures, and the math behind modern machine learning.\n\n - Top Academic Background – Master's degree in CS, ML, AI or related field required; PhD preferred. Equivalent research-level engineering experience also considered.\n\n \n\n\nYOU MIGHT THRIVE IF YOU\n\n - Published or Awarded – First/co-author publications at top-tier venues (NeurIPS, ICML, ICLR, ACL, Interspeech, etc.) or notable competition awards are a strong plus.\n\n - Experimental Mindset – You enjoy exploring open-ended problems and iterating quickly on ideas.\n\n - Bridge Theory \u0026 Practice – You can translate research into systems that work in real-world environments.\n\n - Startup-Ready – You thrive in fast-paced environments with high ownership and ambiguity.\n\n - Collaborative \u0026 Clear Communicator – You can explain complex","salary_min":225000,"salary_max":400000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","pytorch","search","llm","pre-training","speech","research"],"apply_url":"https://jobs.ashbyhq.com/retell-ai/7dbe5404-e08c-4c62-99dc-ef050534d029/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-04-14T05:52:52.3Z","expires_at":"2026-09-29T13:41:58.784656Z","created_at":"2026-04-16T11:17:45.838238Z","updated_at":"2026-08-30T13:41:58.916272Z","company_name":"Retell AI","company_slug":"retell-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=retellai.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/acc5d396-6aa2-40ba-8a49-632774606bde"},{"id":"fdeb7783-851b-48d1-810b-3d39970161b6","company_id":"6ea0f41a-b13e-481a-b410-5195f391f939","title":"Senior Machine Learning Engineer, Voice AI ","slug":"senior-machine-learning-engineer-voice-ai-e60e860b","description":"About the Role \n Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability.\n We're looking for a Senior ML Engineer to drive the model serving layer for voice workloads. You'll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro — pushing latency and throughput to the frontier. You'll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly.\n This is a foundational hire on a small, high-impact team. Voice inference has unique challenges — streaming audio, tokenization, real-time latency budgets — that require dedicated ML engineering focus. You'll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech.\n \n Own the model serving stack that powers Together's voice platform across STT, TTS, and speech-to-speech.\n Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference.\n Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together's infrastructure.\n Build quality evaluation frameworks that guide model selection for customers and inform the roadmap.\n Join a small, early-stage team with outsized impact on a fast-growing product area.\n \n Responsibilities \n \n Optimize inference performance for voice models (STT, TTS, speech-to-speech) — targeting best-in-class TTFB, throughput, and GPU utilization across our curated model set.\n Productionize voice models on serverless and dedicated endpoints, including batching strategies, streaming inference, and memory management tailored to audio workloads.\n Build and maintain a voice model evaluation framework — measuring WER across accents, languages, and noise conditions for STT; naturalness, latency, and pronunciation accuracy for TTS.\n Enable new model architectures in our serving stack as the field evolves, including audio-native LLMs, codec-based models (SNAC), and speech-to-speech systems.\n Collaborate with model partners to integrate and optimize their models (Cartesia, Deepgram, Rime, and others) running on Together's infrastructure.\n Profile and debug performance across the full inference stack — from GPU kernels to framework-level bottlenecks — and ship measurable improvements.\n Work with the platform engineering side of the team to ensure the serving layer meets the latency and reliability requirements of real-time voice APIs.\n Contribute to voice model fine-tuning capabilities (STT and TTS) as we enable customers to build differentiated voice experiences on Together.\n Lay the groundwork for multiple new products down the line.\n \n Requirements \n \n 5+ years of experience in ML engineering, with a focus on model serving, inference optimization, or ML infrastructure.\n Hands-on experience with LLM serving engines (vLLM, SGLang, TensorRT-LLM, or similar) — comfortable reading and modifying engine internals, not just using APIs.\n Strong proficiency in Python and PyTorch; experience with GPU profiling and optimization (CUDA, memory management, kernel-level debugging).\n Track record of shipping ML systems to production with measurable performance improvements.\n Strong product sense — you think about what developers building voice apps actually need, not just what's technically interesting.\n Comfort working on a small, early-stage team where you'll wear multiple hats and move fast.\n Experience with speech and audio ML (ASR, TTS architectures, audio signal processing) is a strong plus but not required — you can learn this quickly if you have strong ML engineering fundamentals.\n Familiarity with audio codecs and tokenization schemes (SNAC, Encodec, DAC) is a plus.\n Experience training or fine-tuning speech models is a plus.\n Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field, or equivalent practical experience\n \n About Together AI \n Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.\n Compensation \n We offer competitive compensation, start","salary_min":200000,"salary_max":260000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["speech","pytorch","llm","fine-tuning","mlops","gpu","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/togetherai/jobs/5088817007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-03-30T19:36:00Z","expires_at":"2026-09-29T13:32:21.767759Z","created_at":"2026-04-13T09:37:38.250213Z","updated_at":"2026-08-30T13:32:21.915057Z","company_name":"Together AI","company_slug":"together-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=together.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fdeb7783-851b-48d1-810b-3d39970161b6"},{"id":"6bdbfae6-b541-4956-99e1-7b2487292755","company_id":"7551b4ca-b2b0-493a-ab58-a15bd9c50393","title":"Lead Engineer - AI Agent Voice Experience ","slug":"senior-machine-learning-engineer-automatic-speech-recognition-asr-31bbe25d","description":"Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day. \n Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. Cresta’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu , founded and led Google's Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences.\n Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta.\n About the role \n We are looking for a Lead Engineer, AI Agent Voice Experience to help build the next generation of AI-powered voice systems for the contact center. In this role, you will work at the intersection of speech, language, and real-time production systems, improving how AI listens, understands, reasons, empathizes, and responds in live customer conversations. \n You will develop and improve machine learning systems that power voice experiences end to end, including automatic speech recognition, turn detection, agentic workflows, voice evaluation, text to speech, speech-to-speech models, and production optimization. You will partner closely with applied researchers, product managers, designers, forward deployed engineers, and platform engineers to ensure model and system improvements translate into measurable customer and business impact.\n This role is ideal for someone who is excited by both model quality and production reality: designing rigorous evaluation frameworks, analyzing failure modes, improving latency and robustness, elevating caller interaction experience, and shipping systems that perform reliably at scale in real-time voice environments.\n Responsibilities \n \n Design, train, evaluate, and deploy machine learning systems that power real-time voice experiences, including speech to text turn detection, text to speech, speech to speech, reasoning and structured insight generation.\n Improve the quality of voice AI systems through error analysis, data curation, metric design, benchmarking, and iterative model improvement, with a strong focus on real-world performance.\n Build evaluation frameworks for complex voice and agentic systems, measuring metrics such as accuracy, robustness, latency, faithfulness, naturalness, professionalism, task completion, and cost.\n Diagnose and mitigate failure modes across the voice stack, including transcription errors, hallucinations, tool misuse, prompt brittleness, context drift, and multi-step reasoning breakdowns.\n Design, implement,  and optimize low-latency ML systems that deliver delightful caller experience (e.g., backchanneling, focusing on foreground speaker, interpreting caller’s emotions, responding with empathy).\n Partner with platform and backend engineers to productionize real-time inference, streaming pipelines, quality monitoring, and continuous model iteration.\n Collaborate cross-functionally with product, design, frontend, and backend teams to integrate voice intelligence seamlessly into Cresta’s platform.\n Mentor engineers, contribute to technical strategy, and help shape the roadmap for Cresta’s voice AI systems.\n \n Qualifications we value \n \n Bachelor’s degree in Computer Science, Mathematics, Machine Learning, AI, or a related field; Master’s or Ph.D. preferred.\n 5+ years of experience building, evaluating, and deploying machine learning systems in production.\n Demonstrated experience in leading fast-moving, highly technical teams. Strong communication skills, with the ability to influence cross-functional decisions and raise the engineering bar.\n Distinctive technical vision for the future of voice AI.\n Strong background in one or more of the following: speech recognition, speech processing, NLP, generative AI, or voice AI.\n Deep experience with model evaluation, benchmarking, error analysis, and quality improvement for production ML systems.\n Solid understanding of transformer-based models, embeddings, retrieval systems, and large-scale training or inference workflows.\n Experience designing and deploying real-time ML systems with strong requirements around latency, scalability, and reliability.\n Experience building data pipelines and tooling for experimentation, measurement, and large-scale quality analysis.\n Ability to work across research and engineering boundaries and translate promising ideas into production-grade systems.\n \n Nice to have \n \n Hands-on experience with ASR quality metrics such as WER and task-level evalu","salary_min":205000,"salary_max":270000,"location":"United States","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["llm","nlp","generative-ai","agents","speech","rag","data-pipeline"],"apply_url":"https://job-boards.greenhouse.io/cresta/jobs/5155675008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-03-17T14:31:23Z","expires_at":"2026-09-29T13:34:38.92458Z","created_at":"2026-04-13T09:39:51.929183Z","updated_at":"2026-08-30T13:34:39.068797Z","company_name":"Cresta","company_slug":"cresta","company_logo_url":"https://www.google.com/s2/favicons?domain=cresta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6bdbfae6-b541-4956-99e1-7b2487292755"},{"id":"f47b2b52-9138-4056-a197-783873a96c39","company_id":"f5ee7284-a657-4da2-b351-cb806a3681cd","title":"Software Engineer - Voice Model","slug":"member-of-technical-staff-voice-model-5b5f6cb9","description":"SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.  Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. \n ABOUT THE ROLE:\n You will join the Grok Voice Model team to help build the world’s best voice AI. We deliver smooth, natural, low-latency spoken interactions — expressive, multilingual, and reliable across devices and real-time scenarios. We own the full training pipeline: massive data curation, premium audio processing, frontier speech-language pre-training, and intensive post-training to push quality, speed, and stability to the limit.\n Our goal: make talking to AI feel like conversing with the most charming, kind, and knowledgeable person imaginable. We’re seeking exceptionally smart, execution-oriented engineers to help us get there.\n RESPONSIBILITIES:\n \n Design and execute large-scale speech data curation and processing pipelines, including collection of diverse real-world audio, synthetic data generation, and automated annotation workflows to enable high-quality model training and evaluation.\n Work on pre-training and post-training of speech-language models, with targeted enhancements through supervised fine-tuning, reinforcement learning, and other techniques to ensure Grok Voice responses are accurate, factually grounded, natural and idiomatic in spoken style, conversational in tone, and fluent across multiple languages.\n Build and iterate a comprehensive evaluation framework covering objective metrics (accuracy, quality, latency, expressiveness), human preference studies, content factuality assessments, real-time interaction quality, and experimentation infrastructure to measure and improve performance.\n Work closely with product teams to integrate voice models into applications and real-time environments, define spoken interaction specifications, and handle the full lifecycle from prototype to global-scale deployment for stable, low-latency, delightful voice experiences.\n \n BASIC QUALIFICATIONS:\n \n Python expert with deep proficiency in writing clean, efficient code for AI/ML systems.\n Hands-on experience processing large-scale datasets using tools like Spark and Ray for cleaning, augmentation, and feature extraction.\n Proficiency in pre-training and post-training speech-language models using JAX/PyTorch, including supervised fine-tuning, reinforcement learning, and optimizations for accuracy, factuality, natural spoken style, detail, and multilingual fluency.\n Ability to set up and run rigorous evaluation pipelines: objective metrics, human preference studies, content factuality checks, and iterative A/B testing to drive model improvements.\n Experience building or working with large-scale distributed training and inference systems on Kubernetes.\n Proactive, self-driven attitude — ready to grind in a fast-paced, high-caliber team to deliver outstanding voice AI experiences.\n \n COMPENSATION AND BENEFITS:\n $150,000 - $450,000 USD\n Base salary is just one part of our total rewards package at SpaceXAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short \u0026 long-term disability insurance, life insurance, and various other discounts and perks.\n SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice .","salary_min":150000,"salary_max":450000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","distributed-systems","reinforcement-learning","speech","pytorch","pre-training"],"apply_url":"https://job-boards.greenhouse.io/xai/jobs/5051966007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-03-16T20:39:18Z","expires_at":"2026-09-29T13:33:53.813235Z","created_at":"2026-04-13T09:38:43.3144Z","updated_at":"2026-08-30T13:33:53.952731Z","company_name":"xAI","company_slug":"xai","company_logo_url":"https://www.google.com/s2/favicons?domain=x.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f47b2b52-9138-4056-a197-783873a96c39"},{"id":"862b6d52-7f6e-451e-9631-3951ac1d6839","company_id":"4d985fa4-b897-4f93-9745-c332367ad86b","title":"Senior Machine Learning Engineer","slug":"senior-machine-learning-engineer-2030adc8","description":"ABOUT RETELL AI\n\nRetell AI is using first-principles thinking to reimagine the call center with cutting-edge voice AI. Thousands of companies now use Retell's AI voice agents to handle sales, support, and logistics calls that once required large teams of human agents. Backed by Y Combinator, Alt Capital, and other leading investors, we've scaled to $80M in ARR with a team of 50, up from $5M at the start of 2025, and are now valued at over $1.5B.\n\nOur vision for 2026 is to build a modern CX platform where entire contact centers are powered by AI. Instead of basic automation that needs constant human tuning, we're creating intelligent AI “workers” that act as frontline agents, QA analysts, and managers, continuously executing, monitoring, and improving every customer interaction.\n\nWe're growing fast and looking for ambitious builders who want to tackle hard technical problems, move quickly, and have a real impact on one of the fastest-growing voice AI companies in the world.\n\nLet's build the future together.\n\nRecent recognition:\n\n - No. 1 Best Places to Work in the Bay Area, San Francisco Business Times 2026 https://finance.yahoo.com/technology/ai/articles/voice-ai-startup-retell-ai-145200025.html\n\n - Top 50 AI Apps, a16z (2025) https://a16z.com/the-ai-application-spending-report-where-startup-dollars-really-go/\n\n - #3 Fastest-Growing Software Company, G2 Best Software Awards 2026 https://company.g2.com/news/g2s-2026-best-software-awards\n\n - Best Agentic AI Software, G2 Best Software Awards 2026 https://www.retellai.com/blog/retell-ai-recognized-as-the-best-agentic-ai-software-by-g2\n\n - #4 Fastest-Growing Software Vendor, Brex Benchmark 2025 https://www.brex.com/journal/brex-benchmark-december-2025\n\n - Enterprise Tech 30 Class of 2026, Nasdaq \u0026 Wing VC https://www.nasdaq.com/videos/retell-ai\n\n - Top-Ranked Startup, Lean AI Leaderboard https://leanaileaderboard.com/\n\n - Backed by Y Combinator https://www.ycombinator.com/companies/retell-ai\n\n \n\n\nABOUT THE ROLE\n\nRetell AI transforms customer experience with voice AI for enterprises, including customers like CVS/Aetna, American Airlines, Lenovo, and Grab. We have more customer stories than we can tell!\n\nThis is a hands-on, high-ownership role for ML engineers who want to build production models that actually ship, and perform under real-world constraints. As a Founding Senior Machine Learning Engineer at Retell, you’ll work across the ML stack to power human-like voice agents that handle millions of real-time phone conversations.\n\nYou’ll fine-tune large language models and audio models, evaluate them with rigorous benchmarks (and human feedback), and deploy them into latency-sensitive, high-traffic systems. You’ll own model performance end-to-end—from training pipelines to post-deployment monitoring—and shape our ML strategy alongside the founding team.\n\nIf you’re excited by hard technical challenges, fast iteration, and the opportunity to define how voice AI works at scale, this role is a rare chance to do it from the ground up.\n\n\n\nKEY RESPONSIBILITIES\n\n - Train \u0026 Tune Models – Fine-tune LLMs and audio models to maximize speed, accuracy, and production-readiness—pushing the frontier of real-time AI voice experiences.\n\n - Benchmark \u0026 Evaluate – Build datasets, define rigorous metrics, and measure model performance across high-impact voice AI tasks to guide development.\n\n - Deploy to Production – Work closely with engineering to ship models, monitor them in the wild, and ensure they stay fast, reliable, and accurate at scale.\n\n - Run Human Evaluations – Build scalable pipelines to collect structured human feedback, benchmark subjective quality, and inform model iterations.\n\n - Level Up Infrastructure – Design and maintain the ML infrastructure needed for fast experimentation, robust training, and continuous deployment.\n   \n\nYOU MIGHT THRIVE IF YOU\n\n - ML Engineer with Real-World Experience – You’ve trained and shipped models in production. Bonus if you’ve worked with LLMs or audio models.\n\n - Fluent in Modern ML Stack – You know your way around Python, PyTorch, and today’s ML tools—from training pipelines to evaluation benchmarks.\n\n - Execution-Oriented – You move fast, take ownership, and focus on solving real problems over perfect ones.\n\n - Startup-Ready – You’re adaptable, resilient, and energized by ambiguity and fast-changing priorities.\n\n - Clear Communicator \u0026 Team Player – You collaborate well across functions and push decisions forward.\n   \n\nJOB DETAILS\n\n - Cash: $225,000 - $325,000 base salary \n\n - Equity: Offers Equity \n\n - Location: Redwood City, CA, US\n\n - US Visas: Retell AI is open to sponsoring work authorization for qualified candidates, including H1B/H-1B, TN, L-1, E-3, F-1 (OPT/CPT), and O-1 visas.\n   \n\nOTHER BENEFITS\n\n - 100% coverage for medical, dental, and vision insurance\n\n - $70/day DoorDash credit for unlimited breakfast, lunch, dinner, and snacks\n\n - $200/month wellness reimbursement (gym,","salary_min":225000,"salary_max":325000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","pytorch","speech","agents","machine-learning"],"apply_url":"https://jobs.ashbyhq.com/retell-ai/dcc921b7-fccc-459a-93c2-10adb4aa147a/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2025-10-16T03:11:50.217Z","expires_at":"2026-09-29T13:41:58.317748Z","created_at":"2026-04-16T11:17:45.347929Z","updated_at":"2026-08-30T13:41:58.455882Z","company_name":"Retell AI","company_slug":"retell-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=retellai.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/862b6d52-7f6e-451e-9631-3951ac1d6839"},{"id":"0f6829fd-cbbb-4bea-aed1-c4406c1879ad","company_id":"dc461dc0-20f9-4429-a009-6cb473fc466c","title":"Senior Software Engineer, Inference","slug":"senior-software-engineer-inference-74ac39bd","description":"Why AssemblyAI \n AssemblyAI builds the best-in-class Voice AI models powering the next generation of voice applications. Our models serve 600M+ inference calls monthly, process 1M+ hours of audio daily, and power 2 billion+ end-user experiences. The Voice AI space is at an inflection point; we’re looking for folks truly excited to join a small team and help define the future of the industry.\n We are one of the most capital-efficient AI companies on the planet - with under 100 people generating roughly $500K ARR per employee, we sit among the top 5 most revenue-dense teams within the fastest-growing AI companies today. That's not an accident; it's a deliberate choice to stay lean, move fast, and give every person on the team outsized ownership and impact. With thousands of customers including Granola, Fireflies, Figure AI, and CallRail, the company has real scale - processing over 2 million hours of audio daily and handling more than 1 million API calls every day. This is a rare growth-stage opportunity where the business is proven and the trajectory is steep, but the team is still small enough that your fingerprints are on everything.\n If you've ever felt buried under layers of bureaucracy, starved of real ownership, or frustrated watching your work disappear into a slow-moving org, AssemblyAI is built differently. The company operates as a true meritocracy, with no heavy planning or approval processes and no gatekeeping on the tools or information you need. For anyone who genuinely cares about voice AI, not as a trend to chase, but as a technology to build,  this is the place where the most interesting problems at the most interesting scale are being solved by a team small enough that you'll actually know everyone's name.\n We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. No matter your race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply!\n About the role: \n We're hiring a Software Engineer to help turn cutting-edge AI research into products our customers rely on every day. You'll sit on a fast-paced engineering team between our research org and our Applied teams, taking new model capabilities from proof of concept to robust, well-documented APIs serving production traffic at scale.\n What You’ll Do: \n \n Design and ship customer-facing APIs that expose new model capabilities, owning them from prototype through launch and ongoing iteration.\n Scale inference infrastructure to support our 1M+ api users\n Partner with researchers to productionize new techniques. For example, turning a notebook or POC into something with the latency, reliability, and ergonomics customers expect.\n Work with our customers and Applied teams to understand how users are building with our products, and feed that back into product design and research direction.\n Contribute across the stack as needed: backend services, inference infrastructure, SDKs, internal tooling.\n \n What You’ll Need: \n \n Strong backend engineering experience, including building and supporting machine learning infrastructure and/or customer-facing APIs in production.\n Comfort operating with ambiguity. Research timelines and product timelines don't always line up, and you're energized rather than frustrated by that.\n Genuine curiosity about AI/ML. You don't need to be a researcher, but you should want to understand what the models are doing well enough to make good engineering decisions around them.\n Strong collaboration skills. You'll be working daily with researchers, applied engineers, and sometimes customers, people with very different contexts and priorities, and the role only works if you enjoy that.\n \n Pay Transparency: \n AssemblyAI strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on paying competitively for our size, stage, and industry, and are one part of many compensation, benefit, and other reward opportunities we provide.\n There are many factors that go into salary determinations, including relevant experience, skill level, qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range.\n The provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range which will be communicated to candidates throughout the interview process.\n Salary range: $190,000 - $225,000\n AI to Interview: \n If you’re selected for an interview, please review this resource to better understand how AssemblyAI appr","salary_min":190000,"salary_max":225000,"location":"North America","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","speech","inference"],"apply_url":"https://job-boards.greenhouse.io/assemblyai/jobs/4728911005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T22:46:09Z","expires_at":"2026-09-29T13:35:16.750171Z","created_at":"2026-08-29T13:35:32.769409Z","updated_at":"2026-08-30T13:35:16.88432Z","company_name":"AssemblyAI","company_slug":"assemblyai","company_logo_url":"https://www.google.com/s2/favicons?domain=assemblyai.com\u0026sz=128","quality_score":85,"url":"https://aidevboard.com/job/0f6829fd-cbbb-4bea-aed1-c4406c1879ad"},{"id":"14d08aa6-ef06-41aa-92a3-1389d23f4e8d","company_id":"95fc9d4d-801c-4800-88aa-1301b340d8f5","title":"Member of Technical Staff, Release Engineer","slug":"member-of-technical-staff-release-engineer-d0336c79","description":"Voice AI that resolves, not transfers.\n\nMost phone systems trap callers in menus and scripts. Vapi is the platform for deploying voice agents that know your business and can listen, adapt, and resolve in minutes.\n\n - The numbers: 1 billion calls. 1 million developers. 10x enterprise ARR growth\n\n - The customers: Amazon Ring, ServiceTitan, New York Life, Intuit, Kavak, and thousands more, from YC startups to the Fortune 500\n\n - The news: a $50M Series B led by Peak XV Partners, with Bessemer Venture Partners, Kleiner Perkins, M12 (Microsoft's Venture Fund), Y Combinator, and our earlier backers. Total raised: $72M\n\n\n\nWhy We’re Hiring This Role:\n\n - Vapi ships hundreds of pull requests a day while serving some of the world’s largest enterprises. Every release must stay fast, safe, observable, and predictable at scale.\n\n - Our CI and deployment systems are critical product infrastructure. We need a senior/staff engineer to remove bottlenecks, repair fragile deploy paths, and increase confidence without slowing product teams.\n\n - You’ll own the systems behind safe releases, including Argo CD, Terraform, and Atlantis—and automate the reliable path. This role focuses on CI/CD, testing, and deployment safety, not primary incident response.\n\n\n\nWhat You’ll Do:\n\n - 30 Days: Map Vapi’s release architecture end to end. Partner with product and infrastructure engineers, baseline CI/test/deploy performance, identify the biggest failure modes, and ship an initial improvement.\n\n - 60 Days: Own the release-tooling roadmap and operating health. Remove the costliest CI/deploy bottlenecks, improve observability and diagnosis, and automate slow or failure-prone workflows.\n\n - 90 Days: Establish a repeatable model for safe, fast releases with measurable gains in validation time, deploy speed, and reliability. Deliver self-service workflows and guardrails, and set the longer-term release-infrastructure roadmap.\n\n\n\nWho You Are:\n\n - Evidence of owning critical CI/CD or release infrastructure at meaningful scale and driving measurable cross-team improvements. We care about impact, not a specific number of years.\n\n - Strong distributed-systems fundamentals and the ability to diagnose failures across build, test, deployment, and infrastructure layers.\n\n - Hands-on experience operating Kubernetes-based delivery systems and infrastructure-as-code tooling such as Argo CD, Terraform, and Atlantis or comparable systems.\n\n - A habit of automating repetitive work, investing in testing and passive defenses, and using data to prove that a system became faster or more reliable.\n\n - Deep curiosity and the ability to gather context quickly, form a clear point of view, and keep pace as the architecture and product evolve.\n\n - A low-ego teammate who communicates clearly and owns outcomes. Familiarity with AI coding tools is expected; experience as an SRE, with development frameworks like multi-agent workflows, and programming languages like TypeScript and Go are a plus.\n\n - This is a full-time, hybrid role in San Francisco.\n\n\n\nHow We Work:\n\n - Build something worthy of love\n   \n   - Craft matters. We aim to build products and experiences customers genuinely love, not just tolerate.\n\n - Commit and follow through\n   \n   - We finish what we start and build trust by being people others can count on.\n\n - Why not today?\n   \n   - We value urgency and momentum. The fastest path to customer value usually wins.\n\n - Seek raw input\n   \n   - We go directly to customers, data, and teammates instead of relying on summaries or assumptions.\n\n - It’s our problem\n   \n   - We operate as one team. We share credit, own mistakes together, and support each other when things get hard.\n\n - Be direct and kind\n   \n   - We give feedback clearly, respectfully, and without delay.\n\n\n\nWhy Vapi:\n\n - Generational impact: Build the human interface for every business\n\n - Ownership culture: Many of us are previous founders\n\n - Kind team: The founders, Jordan and Nikhil, are Canadians\n\n - Tier-1 Investors: YC, KP seed, Bessemer Series A\n\n\n\nWhat We Offer:\n\n - Real stake: $235,000–$280,000 base salary, plus meaningful equity ownership\n\n - Comprehensive health coverage: medical, dental, and vision plans\n\n - Team love: We love hanging out, and we do quarterly off-sites\n\n - Flexible time off: take what you need\n\n - More: catered meals, transportation, equipment, and a $10k annual L\u0026D budget","salary_min":235000,"salary_max":280000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["speech","agents"],"apply_url":"https://jobs.ashbyhq.com/vapi/250ac759-97a6-46b8-ad7c-9bb4f223dd26/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T23:06:23.81Z","expires_at":"2026-09-29T13:42:03.734044Z","created_at":"2026-08-29T13:43:07.958916Z","updated_at":"2026-08-30T13:42:03.871322Z","company_name":"Vapi","company_slug":"vapi","company_logo_url":"https://www.google.com/s2/favicons?domain=vapi.ai\u0026sz=128","quality_score":85,"url":"https://aidevboard.com/job/14d08aa6-ef06-41aa-92a3-1389d23f4e8d"}],"page":1,"per_page":20,"total":221,"total_is_exact":true,"total_pages":12}