{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. 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By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the  expertise , technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed,  built  and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a  realtime , 3D  command  and control center. As the world enters an era of strategic competition, Anduril is committed to bringing  cutting-edge  autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.   \n About the Team:   Air Dominance \u0026 Strike designs, builds, and flies autonomous air vehicles—from  collaborative combat aircraft to expendable cruise missiles and counter-UAS  interceptors. Our vehicles move from whiteboard to first flight on timelines that  traditional primes consider impossible, which means our design cycles live or die  on how fast we can close the iteration loop. The Anduril AI Engineering team  exists to collapse that loop.    \n We are engineers first. We work from engineering first principles and unlock capability through machine learning and AI. We are building to scale across CFD, FEA, thermal, and electromagnetics, with pipelines, architectures, and validation practices that carry across programs.   \n   About the Job   We are looking for a Machine Learning Engineer to apply the latest research in  physics ML to the toughest bottlenecks in our design cycle. This role owns the  entire surrogate modeling stack for Air Dominance \u0026 Strike—the architectures,  the training infrastructure, the simulation data pipelines that feed it, and the  tooling design engineers use to consume predictions.    \n   You will develop, train, and deploy surrogate models that accelerate the physics simulations underpinning our air vehicle programs. Working alongside aerodynamicists, structures engineers, and thermal engineers, your models will directly inform decisions on hardware that actually flies. Where current methods fall short, you will develop new ones, with ample room to identify novel applications of physics ML across our portfolio.    \n   Defense experience is not required. We are looking for engineers who came to machine learning through the complex physical problems they were already trying to solve.    \n   This role is based onsite in our Costa Mesa, CA office.   \n   What You'll Do   \n \n Own the Surrogate Modeling Stack:  Drive the end-to-end design, training, and deployment of production-grade surrogate models to accelerate critical simulation workflows (CFD, FEA, thermal, structural, and aeroelastic) across air vehicle design.   \n Develop State-of-the-Art Architectures:  Design and implement neural architectures tailored to engineering physics, developing new techniques for uncertainty quantification, active learning, and inverse problems (such as geometry and shape optimization).   \n Build Robust Data \u0026 Training Infrastructure:  Create the pipelines behind the training—extracting, aggregating, and sanitizing tens of thousands of high-fidelity results from solver outputs.   \n Optimize \u0026 Integrate:  Optimize inference for the design loop (maximizing GPU utilization, batched evaluation, and interactive-speed latency) and seamlessly integrate surrogate predictions into the tooling our domain engineers already use.   \n Collaborate \u0026 Mentor:  Partner with domain engineers to identify where ML delivers the highest leverage, stay current with Physics AI research, and provide technical mentorship to non ML engineers.   \n \n Qualifications   \n \n Education:  BS, MS, or PhD in aerospace, thermal, mechanical, or electrical engineering, or in machine learning/AI/data science with a demonstrated engineering foundation.   \n Experience:  3+ years of experience taking ML models from R\u0026D into production using large-scale scientific or engineering datasets.   \n Physics ML Expertise:  Working knowledge of modern surrogate architectures (e.g. GNNs, Transolver, DoMINO \u0026 GeoTransolver) comb","salary_min":220000,"salary_max":292000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["payments","tensorflow","distributed-systems","computer-vision","data-pipeline","pytorch","mlops","machine-learning"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5216691007?gh_jid=5216691007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-26T15:59:24Z","expires_at":"2026-09-29T13:37:22.907369Z","created_at":"2026-08-27T13:37:38.482223Z","updated_at":"2026-08-30T13:37:23.045327Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/1a525cd5-6fd1-4af5-be1b-eaa2a3e7709e"},{"id":"241f8621-b66a-4668-ae4c-953914e72085","company_id":"b467c425-56b3-40ce-826a-e603e82a08bd","title":"Senior Software Engineer - Content Understanding","slug":"senior-software-engineer-content-understanding-ab972d21","description":"Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.  \n At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.  \n A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. \n As a Senior Software Engineer within the Creator Organization, you will develop innovative full-stack solutions that define the future of Roblox’s Content Understanding Platform. This platform processes billions of pieces of content—spanning 3D models, audio files, text, video, and entire experiences—extracting structured information about their meaning, context, and relationships. The Content Understanding Team develops cutting-edge AI models, advanced computer vision systems, and highly scalable backend platforms to power search, discovery, and moderation across Roblox. Your contributions will enable seamless asset discovery, automate moderation at scale, and drive transformative generative AI tools that reshape how millions of creators and users engage with Roblox.\n You Will: \n \n Solve full-stack challenges to improve how AI, creators, and users describe and get along with content, including images, 3D models, audio, text, and video.\n Craft and build scalable pipelines for training, evaluating, and deploying machine learning models to support content annotation and discovery.\n Develop robust backend systems to power real-time search, discovery, and powerful generative AI features.\n Blend innovation with practicality, applying the latest AI research to build impactful, production-ready solutions.\n Collaborate with engineers, product managers, and multi-functional teams to deliver bold technical projects.\n \n You Have: \n \n 7 years of strong programming skills in at least two languages (Python, C#, C++, Java) and a willingness to learn others as needed.\n Exposure to front end technologies and frameworks such as React or Angular.\n Practical experience crafting and scaling backend systems in cloud environments.\n Confirmed expertise across the stack, including backend development to deploying ML models in production environments.\n Familiarity with image or 3D object understanding, ideally within gaming or content creation industries.\n A “get stuff done” mentality with a readiness to solve challenges and take on tasks beyond your comfort zone to get results.\n A great foundation in computer vision, AI, or related fields.\n \n You Are \n \n Experience with large-scale search systems, generative AI, or semantic content understanding.\n Experience with modern deep learning frameworks (e.g., PyTorch, TensorFlow) and end-to-end ML workflows.\n Knowledge of 3D geometry or asset workflows.\n Passion for empowering creators through innovative technology.\n For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page .\n Annual Salary Range\n $243,290 — $295,250 USD \n Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).\n Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.\n For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.","salary_min":243290,"salary_max":295250,"location":"San Mateo, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["computer-vision","generative-ai","pytorch","deep-learning","tensorflow"],"apply_url":"https://careers.roblox.com/jobs/8094470?gh_jid=8094470","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-24T22:09:19Z","expires_at":"2026-09-29T13:47:50.815075Z","created_at":"2026-08-25T18:33:06.219084Z","updated_at":"2026-08-30T13:47:50.942237Z","company_name":"Roblox","company_slug":"roblox","company_logo_url":"https://www.google.com/s2/favicons?domain=roblox.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/241f8621-b66a-4668-ae4c-953914e72085"},{"id":"d950a0af-81cc-4c4a-b562-707b97ae1ebb","company_id":"fe4d898e-86f1-400e-95db-988d7f632620","title":"Senior Director, Data","slug":"senior-director-data-460239ea","description":"Position Overview \n As our Senior Director of Data, you will serve as the strategic visionary and executive engine powering our company’s data transformation. In this high-impact leadership role, you will redefine how we leverage information by driving enterprise data strategy, pioneering AI data readiness, commanding end-to-end pipeline engineering, and unlocking competitive advantages through cutting-edge predictive analytics. You will champion, build, and inspire a world-class team across data engineering, analytics, and data science, scaling modern infrastructure, deploying production-grade ML models, and relentlessly embedding a fearless, evidence-based, data-driven culture across every level of the organization. \n Key Responsibilities \n 1. Strategy \u0026 Organizational Data Leadership \n \n \n \n Define and execute the enterprise data, AI data readiness, and analytics strategy aligned with business objectives. \n Champion a data-driven culture across departments by elevating data literacy and self-service analytics. \n Build, mentor, and lead high-performing teams of data engineers, data scientists, and analysts. \n \n \n 2. AI Readiness \u0026 Data Science Leadership \n \n \n \n Drive the AI data strategy, ensuring data is curated, labeled, and optimized for ML/AI model development and deployment. \n Oversee the end-to-end lifecycle of machine learning models, predictive analytics, and feature store infrastructure. \n Collaborate with business partners to identify high-impact AI/ML opportunities that drive strategic value. \n \n \n 3. Pipeline Engineering \u0026 Infrastructure \n \n \n \n Oversee modern data engineering, architectural design, and reliable ETL/ELT pipelines for batch and real-time processing. \n Architect scalable data warehouses, data lakes, and modern data stack operations (MLOps). \n \n \n 4. Governance, Analytics \u0026 Reporting \n \n \n \n Establish governance policies to ensure high data quality, security, and global regulatory compliance (e.g., GDPR, CCPA). \n Deliver key executive dashboards, visualizations, and A/B testing frameworks to measure operational KPIs. \n \n \n Qualifications \n \n Experience: 10+ years of progressive leadership experience across data engineering, analytics, and data science. \n Leadership: Proven track record of managing data engineering and ML teams while fostering a data-driven organizational culture. \n Technical Mastery: Strong hands-on knowledge of Python, SQL, modern ETL tools, cloud data warehouses, and major ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn). \n Architecture \u0026 Pipelines: Deep expertise in pipeline design, streaming data architectures, MLOps, and feature store management. \n Education: Master's or Ph.D. in Data Science, Computer Science, Statistics, or related quantitative field. \n Communication: Excellent capability to translate complex technical concepts into clear strategic insights for non-technical stakeholders. \n The posted pay range represents the anticipated low and high end of the compensation for this position and is subject to change based on business need. To determine a successful candidate’s starting pay, we carefully consider a variety of factors, including primary work location, an evaluation of the candidate’s skills and experience, market demands, and internal parity. For roles with on-target-earnings (OTE), the pay range includes both base salary and target incentive compensation. Target incentive compensation for some roles may include a ramping draw period. Compensation is higher for those who exceed targets. Candidates may receive more information from the recruiter.\n Pay Range\n $194,400 — $432,000 USD \n  \n Navan uses AI-assisted Automated Employment Decision Tool (Metaview) to assist with evaluating resumes against job qualifications for this role. All final decisions are made by human recruiters and hiring managers. \n Human oversight:   Metaview does not automatically reject candidates or make final hiring decisions. Our recruiters and hiring managers review all outputs and make the final hiring decision regarding every application.  \n \n \n Your rights: If you prefer to have your application reviewed without AI assistance, you may request a human evaluation by entering your email here . Your decision to do so will not affect how your candidacy is evaluated. \n \n Please refer to our Candidate Privacy Notice for more information about our processing of personal data, and your rights.","salary_min":194400,"salary_max":432000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["pytorch","tensorflow","mlops","data-pipeline"],"apply_url":"https://navan.com/careers/openings?gh_jid=8145890","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-21T16:58:39Z","expires_at":"2026-09-29T13:48:42.690923Z","created_at":"2026-08-25T18:33:21.168009Z","updated_at":"2026-08-30T13:48:42.820522Z","company_name":"Navan","company_slug":"navan","company_logo_url":"https://www.google.com/s2/favicons?domain=navan.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d950a0af-81cc-4c4a-b562-707b97ae1ebb"},{"id":"ea9ed310-83a0-4da7-92f0-3500ba5c05a5","company_id":"2ca4efa5-edc2-4352-a597-ea27086e1e5b","title":"Senior Machine Learning Engineer, Digital Twin Platform","slug":"senior-machine-learning-engineer-digital-twin-platform-081ecc8d","description":"We're transforming the grocery industry \n At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. \n Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.\n Instacart is a Flex First team \n There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. \n Overview \n The Digital Twin Platform team at Instacart is on a mission to understand exactly what is on store shelves at all times — bringing the precision and depth of a smart warehouse to every local grocery store across North America. Inventory estimates power some of the most critical products at Instacart, from search to logistics, and this team sits at the center of it all. Operating like a startup within a larger company, the team drives the end-to-end shelf data supply chain: ingesting data from retail partners, actively collecting novel inventory observations, developing sophisticated models, and integrating those outputs into live products at scale.\n We are looking for a Senior Machine Learning Engineer to help build the next generation of platforms for understanding, observing, and predicting inventory levels and in-store stocking dynamics in real time. In this role, you will develop machine learning models and deploy them into production systems, working in close collaboration with software engineers, computer vision engineers, product leads, and data scientists. If you're motivated by technically complex, high-impact problems and want to see your work shape how millions of people experience grocery shopping, this is the role for you.\n You can read more about some of the work this team is doing here:\n Introducing New Enterprise AI Solutions to Democratize AI for Grocers of All Sizes \n Instacart Acquires Arpalus to Advance Real-Time Shelf Intelligence \n About the Job \n \n Design, develop, and deploy machine learning models that power real-time understanding of in-store inventory levels and shelf stocking dynamics across thousands of retail locations at scale.\n Own the full ML lifecycle — from problem framing and data exploration through model training, evaluation, and production deployment — with a focus on quality, reliability, and measurable business impact.\n Collaborate cross-functionally with software engineers, computer vision engineers, data scientists, and product leads to bring cutting-edge technologies to the team and drive new product innovation.\n Contribute to building and evolving the core infrastructure of the Digital Twin Platform, including systems that ingest data from retail partners and actively collect novel inventory observations to feed the modeling pipeline.\n Help define the technical direction of an expanding modeling practice on a high-performance team that operates with startup speed — expect ambiguity, changing priorities, and the opportunity to make a significant mark on a problem space that is core to Instacart's business.\n \n About You \n Minimum Qualifications\n \n 5+ years of experience developing and deploying machine learning models in production environments.\n Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.\n Demonstrated experience with large-scale data pipelines and working with structured and unstructured data at scale.\n Experience with cloud infrastructure (AWS, GCP, or Azure) and familiarity with ML platform tooling for model training, versioning, and serving.\n Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or a related technical field, or equivalent practical experience.\n \n Preferred Qualifications\n \n Experience working on computer vision, inventory forecasting, demand sensing, or related spatial/temporal modeling problems.\n Familiarity with real-time inference systems and the architectural considerations of serving ML models in low-latency, high-throughput environments.\n Prior experience in a fast-paced, cross-functional environment where you have independently driven projects from conception through production with limited oversight.\n Exposure to retail, supply chain, or e-commerce domains and an understanding of how inventory data flows an","salary_min":206000,"salary_max":217500,"location":"Remote (Canada)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["pytorch","tensorflow","data-pipeline","computer-vision","fine-tuning","cloud","machine-learning"],"apply_url":"https://instacart.careers/job/?gh_jid=8143147","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T19:12:31Z","expires_at":"2026-09-29T13:39:09.843919Z","created_at":"2026-08-25T18:28:59.914166Z","updated_at":"2026-08-30T13:39:09.978396Z","company_name":"Instacart","company_slug":"instacart","company_logo_url":"https://www.google.com/s2/favicons?domain=www.instacart.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ea9ed310-83a0-4da7-92f0-3500ba5c05a5"},{"id":"f4154f18-d97b-44e2-af31-0a213ace915e","company_id":"2ca4efa5-edc2-4352-a597-ea27086e1e5b","title":"Senior Machine Learning Engineer, Digital Twin Platform","slug":"senior-machine-learning-engineer-digital-twin-platform-85efdb23","description":"We're transforming the grocery industry \n At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. \n Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.\n Instacart is a Flex First team \n There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. \n Overview \n The Digital Twin Platform team at Instacart is on a mission to understand exactly what is on store shelves at all times — bringing the precision and depth of a smart warehouse to every local grocery store across North America. Inventory estimates power some of the most critical products at Instacart, from search to logistics, and this team sits at the center of it all. Operating like a startup within a larger company, the team drives the end-to-end shelf data supply chain: ingesting data from retail partners, actively collecting novel inventory observations, developing sophisticated models, and integrating those outputs into live products at scale.\n We are looking for a Senior Machine Learning Engineer to help build the next generation of platforms for understanding, observing, and predicting inventory levels and in-store stocking dynamics in real time. In this role, you will develop machine learning models and deploy them into production systems, working in close collaboration with software engineers, computer vision engineers, product leads, and data scientists. If you're motivated by technically complex, high-impact problems and want to see your work shape how millions of people experience grocery shopping, this is the role for you.\n You can read more about some of the work this team is doing here:\n Introducing New Enterprise AI Solutions to Democratize AI for Grocers of All Sizes \n Instacart Acquires Arpalus to Advance Real-Time Shelf Intelligence \n About the Job \n \n Design, develop, and deploy machine learning models that power real-time understanding of in-store inventory levels and shelf stocking dynamics across thousands of retail locations at scale.\n Own the full ML lifecycle — from problem framing and data exploration through model training, evaluation, and production deployment — with a focus on quality, reliability, and measurable business impact.\n Collaborate cross-functionally with software engineers, computer vision engineers, data scientists, and product leads to bring cutting-edge technologies to the team and drive new product innovation.\n Contribute to building and evolving the core infrastructure of the Digital Twin Platform, including systems that ingest data from retail partners and actively collect novel inventory observations to feed the modeling pipeline.\n Help define the technical direction of an expanding modeling practice on a high-performance team that operates with startup speed — expect ambiguity, changing priorities, and the opportunity to make a significant mark on a problem space that is core to Instacart's business.\n \n About You \n Minimum Qualifications\n \n 5+ years of experience developing and deploying machine learning models in production environments.\n Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.\n Demonstrated experience with large-scale data pipelines and working with structured and unstructured data at scale.\n Experience with cloud infrastructure (AWS, GCP, or Azure) and familiarity with ML platform tooling for model training, versioning, and serving.\n Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or a related technical field, or equivalent practical experience.\n \n Preferred Qualifications\n \n Experience working on computer vision, inventory forecasting, demand sensing, or related spatial/temporal modeling problems.\n Familiarity with real-time inference systems and the architectural considerations of serving ML models in low-latency, high-throughput environments.\n Prior experience in a fast-paced, cross-functional environment where you have independently driven projects from conception through production with limited oversight.\n Exposure to retail, supply chain, or e-commerce domains and an understanding of how inventory data flows an","salary_min":201000,"salary_max":212000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["cloud","pytorch","computer-vision","fine-tuning","tensorflow","data-pipeline","machine-learning"],"apply_url":"https://instacart.careers/job/?gh_jid=8143145","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T19:12:30Z","expires_at":"2026-09-29T13:39:09.752316Z","created_at":"2026-08-25T18:28:59.910126Z","updated_at":"2026-08-30T13:39:09.886675Z","company_name":"Instacart","company_slug":"instacart","company_logo_url":"https://www.google.com/s2/favicons?domain=www.instacart.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f4154f18-d97b-44e2-af31-0a213ace915e"},{"id":"d29bfaad-c593-4c53-93b1-dff4b4c64a86","company_id":"adc4981a-d4ff-4939-952f-362f51e1291d","title":"Sr. Machine Learning Engineer","slug":"sr-machine-learning-engineer-3ba58cf5","description":"Our Mission: \n 6sense's mission is to multiply what matters: growth, retention, and efficiency.  We envision a future where companies, teams and people reach their full potential.\n Our People: \n People are the heart and soul of 6sense. We serve with passion and purpose. We live by our Being 6sense values of Win as One Team, Stay Curious, Do The Right Thing, Own the Outcome, and Create Belonging.  Every 6sensor plays a part in defining the future of our industry-leading technology.  6sense is a place where difference-makers roll up their sleeves, take risks, act with integrity, and measure success by the value we create for our customers.  We want 6sense to be the best chapter of your career. \n \n About 6sense\n 6sense is Intelligence for Agentic GTM. We turn every signal — yours and ours — into intelligence that every team, tool, and AI agent can act on and trust. Every day, the 6sense Signalverse™ captures one trillion signals to power AI that pinpoints who’s ready to buy, how to engage them, and when to act. 6sense was named a Leader in The Forrester Wave™: Revenue Marketing Platforms for B2B, Q1 2026.\n The Opportunity\n We’re hiring a Senior Machine Learning Engineer to join our AI team, reporting directly to the Head of AI.\n Signals tell you what happened. Our job is to explain why — and that is the problem you will work on. You will build the intelligence that turns a trillion daily signals into cited, explainable answers about why an account matters, why now, and who is deciding. Your models power products customers use every day, including RevvyAI, our conversational GTM intelligence product, and reach their stack through our APIs and MCP server.\n This is a build-and-ship role, not a research role. You will own problems end to end, work directly with Product and Go-to-Market, and see your work reach customers. You’ll join a team distributed across the US and India, at a company where AI is the product rather than a feature.\n What You’ll Do\n \n Own machine learning problems end to end — from data exploration and modeling through deployment, monitoring, and iteration in production.\n Build NLP, LLM, and agentic systems at enterprise scale, including retrieval-based architectures and multi-agent workflows.\n Develop ranking, recommendation, prediction, and optimization models that are explainable rather than black-box.\n Partner with Product and Go-to-Market to turn ambiguous business problems into shipped capabilities.\n Improve the performance, scalability, and reliability of production ML systems, and help shape AI platform architecture.\n Explain your work clearly to technical and non-technical audiences, and engage with customers when needed.\n Mentor engineers and raise the bar for engineering excellence.\n \n What We’re Looking For\n Required\n \n 8+ years of industry experience building and deploying machine learning systems in production, with clear end-to-end ownership.\n Strong foundation in machine learning and applied statistics, with hands-on depth in NLP, transformers, embeddings, and retrieval-based systems.\n Practical experience with modern GenAI tooling such as LangGraph, LangChain, or Amazon Bedrock.\n Strong Python skills and experience building distributed ML pipelines on cloud infrastructure (AWS, Databricks, or equivalent).\n Solid grasp of feature engineering, model evaluation, and MLOps practices.\n A product mindset — you want to build AI products customers use, and you measure yourself on customer impact.\n Excellent communication: you can explain complex technical work clearly, tell the story of what you’ve built and why, and hold your own with product and business partners.\n Comfort with ambiguity and the judgment to drive execution independently.\n \n Nice to Have\n \n Experience with RAG architectures, vector databases, and prompt engineering.\n Hands-on work with PyTorch or TensorFlow.\n Background in B2B SaaS, enterprise AI products, or forward-deployed engineering — especially where you worked directly with complex customer data and delivered quickly.\n \n  \n Base Salary Range: $200,349.50 - $260,912.60. The base salary range represents the anticipated low and high end of the base salary range for this position. Actual salaries may vary and may be above or below the range based on various factors, including but not limited to work location and experience. The base salary is one component of 6sense’s total compensation package for this position. Other compensation may include a bonus program or commission plan, and stock options if approved by 6sense’s board. In addition, 6sense provides a variety of benefits, including generous health insurance coverage, life, and disability insurance, a 401K employer matching program, paid holidays, self-care days, and paid time off (PTO). #Li-remote \n Notice of Collection and Use of Personal Information for California Residents: California Recruitment Privacy Notice and Policy \n Our Benefits:   \n Full-time employees can ta","salary_min":200349,"salary_max":260912,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["tensorflow","nlp","fine-tuning","rag","generative-ai","pytorch","payments","llm"],"apply_url":"https://boards.greenhouse.io/6sense/jobs/8064973?gh_jid=8064973","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T15:47:30Z","expires_at":"2026-09-29T13:41:04.935693Z","created_at":"2026-08-25T18:30:07.718512Z","updated_at":"2026-08-30T13:41:05.080754Z","company_name":"6sense","company_slug":"6sense","company_logo_url":"https://www.google.com/s2/favicons?domain=6sense.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d29bfaad-c593-4c53-93b1-dff4b4c64a86"},{"id":"d5aae1c9-cae9-47d5-9fce-478d44a8cb20","company_id":"4ed3e523-b627-46ed-8dae-04c2ea823be2","title":"Research Scientist/Research Engineer, Reinforcement Learning ","slug":"research-scientistresearch-engineer-reinforcement-learning-2476fcd9","description":"Jump Trading Group is committed to world-class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting-edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivizing collaboration and mutual respect. At Jump, research outcomes drive more than superior risk-adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.\n Our team is a group of quantitative researchers, engineers, and ML experts leading reinforcement learning research and trading at Jump. Our mission is to combine emerging techniques and original research to learn optimal decision-making policies from financial market data and monetize them globally. We are building the future of ML-powered trading through breakthrough reinforcement learning, and we're looking for an exceptional Research Scientist/Research Engineer to join our team.\n What You’ll Do \n As a Research Scientist/Research Engineer working on RL, you'll be at the forefront of applying reinforcement learning to markets. You'll conduct original research and own the systems that turn it into production trading: designing and evaluating policy architectures, reward formulations, and objective horizons with rigorous out-of-sample benchmarking; partnering with trading and research teams to source, integrate, and validate their alpha signals within the RL framework; ensuring simulation fidelity against live trading by modeling market microstructure, fill dynamics, liquidity, and latency; building efficient tooling to store, process, and analyze very large volumes of market and signal data; and communicating findings to technical and trading audiences. This isn't incremental optimization; we're pushing the boundaries of what reinforcement learning can do at scale, where your improvements directly impact live trading.\n Other duties as assigned or needed. Skills You’ll Need \n \n 5+ years of experience developing reinforcement learning and/or deep learning systems with measurable impact in industry and/or academia\n Depth in reinforcement learning, including experience designing reward formulations, policy architectures, and evaluation, and taking RL methods from research into production\n Proficiency in Python and/or C++\n Familiarity with ML libraries/frameworks such as PyTorch (preferred), TensorFlow, and/or JAX\n Strong foundation in mathematics and statistics\n PhD or Master's degree in Computer Science, Machine Learning, Robotics (or a related subject)\n Strong publication record at ICML, ICLR, AAAI, NeurIPS, CVPR, or equivalent\n Ability to thrive in a collaborative, team-oriented environment\n Creative thinkers who are driven, self-motivated, and eager to solve challenging problems\n Reliable and predictable availability\n Excellent written and verbal communication skills in English\n Benefits \n \n Discretionary bonus eligibility \n Medical, dental, and vision insurance \n HSA, FSA, and Dependent Care options \n Employer Paid Group Term Life and AD\u0026D Insurance \n Voluntary Life \u0026 AD\u0026D insurance \n Paid vacation plus paid holidays \n Retirement plan with employer match \n Paid parental leave \n Wellness Programs \n \n Annual Base Salary Range \n $200,000 — $350,000 USD","salary_min":200000,"salary_max":350000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pytorch","tensorflow","search","deep-learning","reinforcement-learning","robotics","research"],"apply_url":"https://www.jumptrading.com/hr/job?gh_jid=8122860","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-18T18:54:10Z","expires_at":"2026-09-29T13:47:31.484855Z","created_at":"2026-08-27T13:48:12.175153Z","updated_at":"2026-08-30T13:47:31.614748Z","company_name":"Jump Trading","company_slug":"jump-trading","company_logo_url":"https://www.google.com/s2/favicons?domain=jumptrading.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d5aae1c9-cae9-47d5-9fce-478d44a8cb20"},{"id":"81953b3d-cc3a-4228-ae1e-64c78614ff45","company_id":"e455f75a-a424-4955-9844-afebe8ea6eb4","title":"Staff Machine Learning Engineer, Generative AI (Auth0)","slug":"staff-machine-learning-engineer-generative-ai-auth0-d6e0713c","description":"Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.\n The Team :\n Have you ever considered what powers the intelligent features behind seamless product experiences? The GenAI team is at the forefront of enabling AI-powered security and intelligent innovation across our organization. From crafting AI powered security services, to intuitive generative AI-powered chat experiences that provide instant product support, and developing the best developer experience around authentication for generative AI and AI agents, our team is instrumental in bringing the transformative power of AI to life. We collaborate closely with the Machine Learning team and various product teams to ensure the seamless and secure delivery of AI-enhanced features that provide real value to our users.\n The Opportunity : \n As a Staff Machine Learning Engineer on the Generative AI team, you will help shape, architect, and accelerate our Generative AI strategy by contributing across the stack of model development, infrastructure, and platform services. You’ll drive design and implementation of production-ready AI/ML systems at scale: ranging from LLM-powered features to reusable components that other teams across Okta can build on.\n You will have the opportunity to: \n \n Architect, design, and deploy robust Machine Learning \u0026 GenAI systems, ensuring seamless integration with diverse platform services and establishing scalable LLMOps pipelines in production.\n Drive technical decision making while striving to hit the right balance between factors such as simplicity, flexibility, reliability, and performance.\n Lead initiatives to tune, optimize, and deploy agentic applications in production with a focus on performance, reliability, and security.\n Partner with Product, Security, and Platform Engineering teams to design AI-powered experiences that are both innovative and trustworthy.\n Design and implement scalable infrastructure and platform services for large-scale Generative AI use cases.\n Collaborate cross-functionally with product managers, researchers, and engineers to deliver secure, high-quality, and scalable AI/ML systems.\n \n   What you will do: \n \n Spearhead the design of scalable, observable ML and Generative AI systems that integrate retrieval, inference, and evaluation pipelines.\n Develop and iterate on structured prompting, context retrieval, and RAG workflows that improve accuracy, safety, and cost efficiency in Claude-based systems.\n Build and refine automated evaluation pipelines to measure model quality, correctness, groundedness, and safety in production.\n Implement schema validation, structured output enforcement, and other guardrails that keep AI outputs reliable, auditable, and compliant with enterprise standards.\n Mentor and coach engineers, contributing to the growth of the team and the larger engineering community.\n \n What you bring: \n \n 7+ years of software development experience, with strong programming expertise in Python (and familiarity with Go or Typescript a plus).\n Hands-on experience with applied machine learning, from feature engineering to training and fine-tuning models.\n Hands-on experience with modern Generative AI platforms (AWS Bedrock, OpenAI, Anthropic, etc.).\n Deep understanding of retrieval-augmented generation (RAG), embeddings, and knowledge-base workflows.\n Hands-on experience with LiteLLM, LangGraph, LangChain, LlamaIndex, MCP, or other related AI agent frameworks.\n Familiarity with ML frameworks (FastAPI, PyTorch, TensorFlow, Spark ML) and workflow orchestration tools (Airflow, etc.).\n Experience defining evaluation metrics, pipelines, and feedback loops for ML/GenAI systems.\n Proven ability to collaborate with product and engineering teams to drive greenfield initiatives forward, navigate unknowns, and iterate quickly and frequently.\n Experience building tools or infrastructure for AI/ML applications, with a deep understanding of the developer lifecycle in an AI-native world.\n \n Nice to haves: \n \n Experience integrating AI-driven systems with identity, authentication, or security products.\n Exposure to ethical AI, model risk, or compliance frameworks.\n Familiarity with evaluation datasets, synthetic data generation, or LLM-as-a-judge methods.\n \n Please note that we encourage candidates to apply even if you do not have experience with all of the criteria or technologies listed above; these are provided to give insight into the tech stack and general responsibilities for the role.\n  \n #LI-HYBRID #LI-SH1 P-2652_3522731\n  \n Below is the ann","salary_min":168000,"salary_max":231000,"location":"Toronto, Canada","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","cloud","llm","pytorch","tensorflow","rag","generative-ai","fine-tuning"],"apply_url":"https://www.okta.com/company/careers/opportunity/8139696?gh_jid=8139696","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-18T18:30:11Z","expires_at":"2026-09-29T13:39:37.497094Z","created_at":"2026-08-25T18:29:14.49005Z","updated_at":"2026-08-30T13:39:37.630778Z","company_name":"Okta","company_slug":"okta","company_logo_url":"https://www.google.com/s2/favicons?domain=okta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/81953b3d-cc3a-4228-ae1e-64c78614ff45"},{"id":"b04c0a03-fc25-4cc1-85e1-9c6efc357643","company_id":"97187e1c-a220-4e7e-aa1e-cd5342f434c1","title":"Machine Learning Engineer","slug":"machine-learning-engineer-50e35dc4","description":"Who we are \n About Stripe \n Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.\n What you’ll do \n Responsibilities \n \n Design state-of-the-art ML models and large-scale ML systems for underwriting and portfolio management for Stripe Capital based on ML principles, domain knowledge, risk, regulatory and engineering constraints. \n Design systems to speed up the time from idea to deployment of new models. \n Experiment and iterate on ML models (using tools including PyTorch and TensorFlow) to achieve key business goals and drive efficiency. \n Develop pipelines and automated processes to train and evaluate models in offline and online environments. \n Integrate ML models into production systems and ensure their scalability and reliability. \n Collaborate with product and strategy partners to propose, prioritize, and implement new product features. \n Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions.\n \n Who you are \n Minimum requirements \n Must have a Bachelor's degree or foreign equivalent in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field, plus two (2) years of experience in Building and shipping ML systems in production.\n Must have two (2) years of experience in each of the following:\n \n ML algorithms and model architectures;\n Designing, training and evaluating machine learning models;\n Productionizing and deploying machine learning models at scale;\n Orchestrating data pipelines and leveraging large-scale datasets; and\n Building and deploying ML models to solve business problems.\n \n Must have one (1) year of experience in each of the following:\n \n ML libraries and frameworks including PyTorch, TensorFlow, XGBoost or Spark; and\n Deep learning, including transformers, test-time compute, or reinforcement learning.\n \n Salary: $212,000 - $318,000/yr.  \n This salary range represents the base salary range for the role and any sales commissions / sales bonuses targets, if applicable, would be in addition to the base salary.\n 40 hrs/week\n 50% Telecommuting Permitted.\n Multiple Positions Available. \n Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends. CA29 \n #LI-DNI","salary_min":212000,"salary_max":318000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["reinforcement-learning","tensorflow","pytorch","deep-learning","data-pipeline","payments","machine-learning"],"apply_url":"https://stripe.com/jobs/search?gh_jid=8137997","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-17T22:06:29Z","expires_at":"2026-09-29T13:34:35.944205Z","created_at":"2026-08-25T18:27:17.935027Z","updated_at":"2026-08-30T13:34:36.087082Z","company_name":"Stripe","company_slug":"stripe","company_logo_url":"https://www.google.com/s2/favicons?domain=stripe.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b04c0a03-fc25-4cc1-85e1-9c6efc357643"},{"id":"a27af2e3-0c1e-45a0-8d92-2485073e28ff","company_id":"12105b3e-eb1d-4a92-95b6-855042facaf1","title":"Applied Scientist II","slug":"applied-scientist-ii-c3c7e3aa","description":"At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers. When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing.\n Applied Scientist II \n  \n Why We Have This Role \n We are looking for talented and innovative Applied Scientist to bring our Core AI Machine Learning and Artificial Intelligence R\u0026D and strategy to the next level. Our goal is to personalize the Qualtrics experience using ML and AI features showcasing Qualtrics data as a core value proposition and competitive advantage.\n As an Applied Scientist at Qualtrics, you should love building cutting-edge predictive models to solve hard customer problems. Crafting models in an agile environment to withstand hyper growth and owning quality from end-to-end is a rewarding challenge and one of the reasons Qualtrics is such an exciting place to work!\n How You’ll Find Success \n \n Leverage your deep knowledge of artificial intelligence (AI) principles, including machine learning, natural language processing, computer vision, and reinforcement learning.\n Use your understanding of both supervised and unsupervised learning techniques, and their applications in building intelligent systems.\n Develop and optimize algorithms for building scalable and efficient GenAI applications.\n Tackle challenging problems in creative ways, leveraging generative models to address real-world use cases and drive innovation.\n Use effective communication skills to articulate technical concepts to non-technical stakeholders and gather requirements for GenAI application development.\n Show strong programming skills in languages like Python, along with proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar.\n \n How You’ll Grow \n \n Passion for leveraging cutting-edge AI technology to create innovative GenAI applications that have a meaningful impact on businesses, industries, and society.\n Commitment to developing GenAI applications that adhere to ethical standards and promote positive societal impact while minimizing potential risks.\n Drive to push the boundaries of what's possible with AI, and to contribute to the advancement of the field through research, experimentation, and collaboration.\n Willingness to stay updated with the latest advancements in AI research and technology, and to continuously learn and adapt to new methodologies and best practices.\n Agility to pivot and iterate on GenAI applications based on feedback, emerging trends, and changing business requirements.\n \n Things You’ll Do \n \n Address challenges in products through Large Language Models, Deep Learning and Data Science approaches and publish research papers.\n Work as part of a multidisciplinary team to research, implement, evaluate, optimize, productize and maintain cutting-edge machine learning models to meet the demands of our rapidly growing business\n Stay on top of the latest developments in machine learning and related research, and present research findings with the broader community\n Work closely with, and incorporate feedback from other specialists, engineers, and product managers\n Lead and engage in design reviews, modeling discussions, requirement definitions and other technical activities in diverse capacity\n Contribute to and inspire the Conversational AI, NLP, and Data Science technology roadmap at Qualtrics.\n Design, build, and evaluate Agentic AI systems to solve complex customer challenges.\n \n What We’re Looking For On Your Resume \n \n Bachelors and Ph.D in Computer Science or related fields\n Solid understanding of machine learning fundamentals and tool ecosystem\n 3+ years of combined academic and industrial research experience in machine learning, NLP, information retrieval, deep learning or a related field.\n Experience with Agentic AI systems, including design, development, and rigorous evaluation of agent performance.\n Deep learning implementation expertise (TensorFlow, PyTorch etc)\n Excellent command of at least one modern programming language (preferably Python)\n Deep understanding of machine learning model life cy","salary_min":155000,"salary_max":203500,"location":"Reston, VA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["llm","search","tensorflow","deep-learning","fine-tuning","agents","computer-vision","healthcare"],"apply_url":"https://www.qualtrics.com/careers/us/en/job/8115079?gh_jid=8115079","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-17T18:10:13Z","expires_at":"2026-09-29T13:49:13.405443Z","created_at":"2026-08-25T18:33:38.583782Z","updated_at":"2026-08-30T13:49:13.540253Z","company_name":"Qualtrics","company_slug":"qualtrics","company_logo_url":"https://www.google.com/s2/favicons?domain=qualtrics.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a27af2e3-0c1e-45a0-8d92-2485073e28ff"},{"id":"f5ed0945-789e-4523-9377-609285671969","company_id":"74257563-5513-4a8d-a0f7-01f00c59aed6","title":"Senior Machine Learning Engineer, Trust","slug":"senior-machine-learning-engineer-trust-af806995","description":"Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. \n The Community You Will Join: \n Everyone at Airbnb thinks about trust, but our team obsesses over it daily. At the core of trust is safety, and thus we spend a significant amount of our time and energy keeping the community safe. The Trust team is responsible for developing the technology that helps protect our community and platform from fraud while also ensuring our hosts, guests, homes, and experiences meet our high standards. We constantly work to fight against online fraud (such as monetary loss, compromised accounts, spam and scam in messages, fake inventory, etc.) as well as offline fraud (theft, property damage, personal safety, etc.). We also work on onboarding and screening of users, and think about complex topics like identity and reputation to ensure that every interaction with Airbnb helps build trust in us and our community.\n The Trust Frontier AI team is where new AI technology for Trust gets invented and proven. We build specialized models for mission-critical trust and safety problems, develop the AI agents and agentic capabilities that automate trust decisions, and create the benchmarks and evaluation harnesses that keep decision quality high as those agents take on more autonomy. We work on problems before the answer is known — prototyping, experimenting, and iterating with our partner teams until a solution proves itself against real business and top line metrics.\n You'll work side-by-side with talented product managers, data scientists, software engineers, fraud intelligence, and operations teams. Together, you'll design and build ML solutions that have direct, meaningful impact on user trust, business success, and the global Airbnb community.\n The Difference You Will Make: \n As a Senior Machine Learning Engineer on the Trust Frontier AI team, you will actively contribute code and ideas that shape the next generation of AI systems protecting millions of Airbnb users. You'll own and deliver ML projects end-to-end, from framing an ambiguous problem and prototyping a solution, to training and productionizing models, to proving impact on top line metrics with front line teams.\n You'll work on abuse behavior detection that spans multiple defenses, on AI agents that make trust decisions autonomously, and on the evaluation and benchmarking work that makes those decisions trustworthy. Much of this work is early: you will help decide what to build, not only how to build it, and you'll see it through to measurable impact on the platform.\n A Typical Day:  \n \n Frame and prototype ML and agentic solutions for problems that do not yet have an established approach, in partnership with product managers, data scientists, and front line defense teams.\n Design, build, and productionize end-to-end Machine Learning pipelines — including feature engineering, model training, evaluation, and deployment — for both batch and real-time use cases.\n Build and improve abuse behavior detection that generalizes across defenses.\n Design, launch, and iterate on AI agents that automate trust decisions, including orchestration, tool interfaces, and the guardrails that hold quality steady as autonomy increases.\n Build benchmarks, evaluation harnesses, and instrumentation that let us measure agentic and model decision quality objectively, and use them to drive real improvements.\n Develop specialized models for trust and safety use cases, and use LLMs and AI agents to accelerate how we build models.\n Write, review, and ship clean, testable code — whether training a new model, improving an existing pipeline, or optimizing a feature for scalability and reliability.\n Work with large-scale structured and unstructured data to continuously improve ML models for Airbnb product, business, and operational use cases.\n Partner with front line defense teams to validate solutions through experiments and holdouts, and quantify their impact on business and operational metrics.\n Participate in code reviews, design discussions, and cross-team collaborations to contribute to a high-quality ML engineering culture.\n \n Your Expertise: \n \n 5-10 years of industry experience in applied Machine Learning, with a track record of building and productionizing models at scale.\n 1-2+ years of hands-on experience with LLMs and GenAI technologies, including building with agentic frameworks, orchestration, and evaluation.\n Strong programming skills in Python (required) and familiarity with Scala, Java, or equivalent.\n Solid understanding of Machine Learning best practices — e.g., training/serving skew minimization, A/B testing, feature engineering, model selection — and algorithms such as ","salary_min":200000,"salary_max":235000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["tensorflow","data-pipeline","agents","pytorch","generative-ai","llm","deep-learning","machine-learning"],"apply_url":"https://careers.airbnb.com/positions/8130355?gh_jid=8130355","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-14T21:27:57Z","expires_at":"2026-09-29T13:39:39.773826Z","created_at":"2026-08-25T18:29:15.515072Z","updated_at":"2026-08-30T13:39:39.906905Z","company_name":"Airbnb","company_slug":"airbnb","company_logo_url":"https://www.google.com/s2/favicons?domain=airbnb.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f5ed0945-789e-4523-9377-609285671969"},{"id":"b25eefc5-b8c1-4baf-9494-64c7a4eca526","company_id":"c93e0284-9c76-4a85-9905-494865ab9278","title":"Principal Compiler Engineer ","slug":"senior-principal-compiler-engineer-a021a7d0","description":"The era of pervasive AI has arrived. In this era, organizations will use generative AI to unlock hidden value in their data, accelerate processes, reduce costs, drive efficiency and innovation to fundamentally transform their businesses and operations at scale. \n SambaNova Suite™ is the first full-stack, generative AI platform, from chip to model, optimized for enterprise and government organizations. Powered by the intelligent SN40L chip, the SambaNova Suite is a fully integrated platform, delivered on-premises or in the cloud, combined with state-of-the-art open-source models that can be easily and securely fine-tuned using customer data for greater accuracy. Once adapted with customer data, customers retain model ownership in perpetuity, so they can turn generative AI into one of their most valuable assets. \n About the team \n The compiler team at SambaNova powers the RDU through a unique compilation strategy. By fusing kernels into dataflow graphs that run across the entire accelerator architecture, we avoid sequential kernel launches and eliminate the memory traffic that bottlenecks conventional hardware. This is a key differentiator and unlike any other product on the market. \n About the role \n As a Principal Compiler Engineer you'll lead critical areas of our compiler including the IR and pass infrastructure, model lowering and partitioning, tensor tiling, memory management, and mapping operations onto the fabric. You'll operate in a tightly coupled environment, influencing hardware design to optimize performance, and bring the technical judgement, cross functional diplomacy, foresight, and low-level programming depth that integrated system design demands. You'll work with senior team members to ensure career growth and engagement, mentor and develop early career talent, actively recruit for the organization, and participate in interviews.\n Responsibilities \n \n Lead compiler engineering through ensuring standard methodologies, enterprise product insertion and process evolution\n Work with peers, domain experts, developers, customers, and work across the enterprise seeking optimal solutions\n Develop, integrate, and implement products\n Provide support for proposals in key areas aligned with core team competencies\n \n Basic Qualifications \n \n Bachelor’s or Master’s Degree in Computer Science, Computer Engineering, or equivalent with 5-10 years of industry experience\n \n Additional Qualifications \n \n Deep theoretical understanding of compiler fundamentals\n Experience building and deploying software products\n Experience with one or more deep learning frameworks (i.e. TensorFlow, PyTorch) is a plus\n Experience with common compiler development practices and methodologies\n Excitement about high-performance systems engineering and performance debugging\n An appreciation for process and developing cross-disciplinary collaboration\n \n Preferred Qualifications \n \n Experience with MLIR\n Familiarity with machine learning models and frameworks\n Familiarity with accelerated computing\n Exposure to dataflow architectures\n Base Salary Range:\n Base Pay Range\n $180,000 — $255,000 USD \n Submission Guidelines Please note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified.  \n EEO Policy SambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. \n Benefits Summary for US-Based, Full-Time Employment Positions SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD\u0026D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.","salary_min":180000,"salary_max":255000,"location":"Austin, TX","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["tensorflow","deep-learning","pytorch","generative-ai"],"apply_url":"https://sambanova.ai/sambanova-available-positions/?gh_jid=6007939004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-14T13:58:02Z","expires_at":"2026-09-29T13:34:49.224959Z","created_at":"2026-08-25T18:27:21.859841Z","updated_at":"2026-08-30T13:34:49.359418Z","company_name":"SambaNova Systems","company_slug":"sambanova","company_logo_url":"https://www.google.com/s2/favicons?domain=sambanova.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b25eefc5-b8c1-4baf-9494-64c7a4eca526"},{"id":"8cf9f724-5543-42e5-8ec7-6e485eeeb0a4","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Senior Machine Learning Infrastructure Engineer, Embedding Platform","slug":"senior-machine-learning-infrastructure-engineer-embedding-platform-6b3a54da","description":"Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .\n The LS Embedding Machine Learning Platform team is at the forefront of building highly expressive, machine learning models that power Reddit’s recommendation systems. We go beyond standard retrieval and ranking architectures, leveraging modern deep learning approaches and scalable model designs to enhance personalization across Reddit’s ecosystem. Our work impacts content discovery, user engagement, and platform growth at a massive scale.\n About the Role \n As a Senior Machine Learning Infrastructure Engineer , you will work across both model development and ML platform to build large-scale learning systems that improve recommendation and personalization on Reddit. At the senior level, you will own major technical components end to end: designing models, implementing training and evaluation pipelines, and driving production deployment in close partnership with ML platform, product, and cross-functional ML teams.\n Responsibilities \n \n Design, train, and improve large-scale machine learning platforms for recommendation or personalization systems.\n Own and deliver major ML systems components end to end, from problem framing through production rollout.\n Build and optimize end-to-end ML pipelines spanning data preparation, feature generation, training, evaluation, and deployment.\n Improve distributed training, model efficiency, and online inference performance.\n Apply modern modeling approaches including sequence modeling and related foundation-model techniques to Reddit use cases.\n Develop reliable serving and monitoring patterns for low-latency, high-throughput production ML systems.\n Work with cross-functional partners across product, relevance, ads, and core ML teams to deliver measurable improvements in user experience and business impact.\n Drive rigorous offline and online evaluation, including experimentation, model diagnostics, and feedback-loop improvement.\n Contribute to engineering quality through strong code, design reviews, documentation, and operational excellence.\n \n Qualifications \n \n 5+ years of experience in machine learning engineering, with a strong focus on large-scale ML infrastructure and recommendation or personalization systems.\n Expertise in modern deep learning architectures, including sequence models and foundational models.\n Experience building or scaling ML platform for large datasets and high-traffic production environments.\n Demonstrated ability to independently scope and execute ambiguous technical work, while owning high-quality implementation details.\n Solid understanding of distributed training and inference concepts, such as data parallelism, model parallelism, pipeline parallelism, or related optimization techniques.\n Proficiency in Python and experience with modern ML frameworks such as PyTorch, TensorFlow, or similar.\n Strong software engineering fundamentals, including system design, debugging, testing, and performance optimization.\n Experience with A/B testing, model evaluation frameworks, and real-time feedback loops in large-scale production systems.\n Excellent communication skills, with the ability to effectively present complex ML concepts to technical and non-technical stakeholders.\n \n Benefits: \n \n Comprehensive Healthcare Benefits and Income Replacement Programs\n 401k with Employer Match\n Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support\n Family Planning Support\n Gender-Affirming Care\n Mental Health \u0026 Coaching Benefits\n Flexible Vacation \u0026 Paid Volunteer Time Off\n Generous Paid Parental Leave \n \n #LI-Remote\n Pay Transparency: \n This job posting may span more than one career level.\n In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ .\n To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, ","salary_min":190800,"salary_max":267100,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["healthcare","pytorch","deep-learning","distributed-systems","tensorflow","infrastructure","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/8127022","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-12T23:02:49Z","expires_at":"2026-09-29T13:38:58.366394Z","created_at":"2026-08-25T18:28:56.636852Z","updated_at":"2026-08-30T13:38:58.502511Z","company_name":"Reddit","company_slug":"reddit","company_logo_url":"https://www.google.com/s2/favicons?domain=www.reddit.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8cf9f724-5543-42e5-8ec7-6e485eeeb0a4"},{"id":"8734987a-57e2-4dbd-9ce9-54ac7fc10411","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Senior Data Scientist, Ads","slug":"senior-data-scientist-ads-a6497d93","description":"Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .\n Location: US remote-friendly \n Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.\n Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.\n About the Ads Data Science Team: \n The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. \n We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.\n About the Role: \n We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.\n Responsibilities: \n \n Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform\n Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform\n Collaborate with product managers and engineers to define product requirements and translate them into data science solutions\n Develop ML models \u0026 DS methods to improve anomaly detection, prediction, \u0026 pattern recognition \n Communicate findings and recommendations to stakeholders across the organization\n Stay up-to-date on the latest advancements in machine learning and data science\n Mentor and guide junior data scientists on the team\n \n Qualifications: \n \n Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research\n For M.S. holders: 5+ years of industry experience in applied science or data science roles\n For Ph.D. holders: 4+ years of industry experience in applied science or data science roles\n Platform experience and a deep understanding of the ads ecosystem\n Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design\n Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus\n Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch\n Experience with SQL and relational databases\n Excellent communication and presentation skills\n Passion for Reddit and the online advertising industry\n \n Bonus Points: \n \n Experience with online advertising and ad tech\n Experience with causal inference and A/B testing\n Contributions to open-source projects or publications in relevant conferences or journals\n \n Benefits: \n \n Comprehensive Healthcare Benefits and Income Replacement Programs\n 401k with Employer Match\n Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support\n Family Planning Support\n Gender-Affirming Care\n Mental Health \u0026 Coaching Benefits\n Flexible Vacation \u0026 Paid Volunteer Time Off\n Generous Paid Parental Leave  \n \n  \n #LI-Remote\n Pay Transparency: \n This job posting may span more than one career level.\n In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for ","salary_min":190800,"salary_max":267100,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["healthcare","tensorflow","pytorch","data-science"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/8104403","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-12T22:32:15Z","expires_at":"2026-09-29T13:38:57.619454Z","created_at":"2026-08-25T18:28:56.611251Z","updated_at":"2026-08-30T13:38:57.752182Z","company_name":"Reddit","company_slug":"reddit","company_logo_url":"https://www.google.com/s2/favicons?domain=www.reddit.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8734987a-57e2-4dbd-9ce9-54ac7fc10411"},{"id":"94b0d6ed-331e-4eaf-97b4-93754391e8c4","company_id":"76758213-26fd-4192-9dd8-7ffc02a855c1","title":"Principal Software Engineer (Libraries Platform) ","slug":"principal-software-engineer-libraries-platform-44c3c88c","description":"Chainguard is the trusted source for open source. By delivering hardened, secure, and production-ready builds of all the open source software engineers and AI agents rely on, Chainguard helps organizations build faster, stay compliant, and eliminate risk.  Our customers include Fortune 500 enterprises and global industry leaders, including Anduril, Canva, Fortinet, Hewlett Packard Enterprise, OpenAI, Snap Inc., and Snowflake. Chainguard is venture-backed by leading investors, including Amplify, IVP, Kleiner Perkins, Lightspeed Venture Partners, Mantis VC, Redpoint Ventures, Sequoia Capital, and Spark Capital.\n Principal Software Engineer, (Libraries Platform) \n The role:  \n At Chainguard, we think the best platform work is invisible: the libraries just appear, the builds just work, and the CVEs quietly regret their life choices.\n Chainguard's Libraries organization runs the secure, reliable factory that continuously builds, verifies, and serves open-source libraries to customers and internal teams across multiple ecosystems. We're expanding that factory to new inbound ecosystems, while raising the bar on how much of the remediation and build lifecycle runs without a human in the loop.\n As a Principal Software Engineer on the Libraries Platform team, you'll set technical direction for that expansion. This is a strategic, cross-organizational platform role: you're not just operating the existing factory, you're deciding how it generalizes to ecosystems it wasn't originally built for, and how much of the remediation pipeline - from CVE detection through patch, rebuild, verification, and release - can become fully automated rather than engineer-mediated. Your decisions will shape the platform's architecture for years and influence how every ecosystem team builds on top of it.\n What you’ll do: \n \n \n Own the technical strategy for multi-ecosystem scaling. Define the architecture that lets the Libraries Platform onboard new language ecosystems (.NET, Go, Rust) without re-deriving core services per ecosystem: generalizing package indexing, build orchestration, and metadata services so they're ecosystem-agnostic where possible and cleanly extensible where not.\n \n Drive end-to-end remediation automation. Lead the redesign of CVE remediation workflows to close the loop from detection to verified, released fix with minimal manual intervention, rebuild triggering, SBOM and provenance regeneration, policy verification, and rollout, across all supported ecosystems.\n \n Push the frontier on novel patch generation. Set the direction for agentic/AI-driven systems that synthesize security fixes when no upstream patch exists yet — not just selecting or backporting existing ones — and design the guardrails (automated validation, regression testing, provenance, and human checkpoints) that make machine-generated patches safe to ship across ecosystems.\n \n Set platform-wide technical direction, spanning the package index, build/packaging pipelines, registry mirrors, and orchestration tooling that serve external customers and internal ecosystem teams at scale.\n \n Make foundational build vs. buy and sequencing calls for bringing .NET, Go, and Rust online, identifying what's genuinely novel about each ecosystem's toolchain, packaging, and dependency model, and what can reuse or extend existing platform primitives.\n \n Partner at the org level with Ecosystem teams (Java, JavaScript, Python/AI/ML, and new-language leads), Platform, Delivery, Sustaining, and Security to align the platform roadmap with where the business is taking on new ecosystem risk and commitments.\n \n Raise the technical bar across the org: mentor Staff and Senior Engineers, drive design reviews for the biggest architectural bets, and write the docs and RFCs that let other teams build correctly on the platform without you in the room.\n \n Own reliability and scalability at the platform level: define SLOs for the expanded remediation pipeline, and lead incident response and postmortems for the platform's most consequential failures.\n \n Get hands-on when it matters: dig into toolchain, compiler, and dependency-resolution problems specific to new ecosystems (e.g., NuGet, Go modules, Cargo) when they threaten the pipeline's reliability or timeline.\n \n What we’re looking for: \n \n \n 12+ years designing, building, and operating infrastructure for language ecosystems or developer platforms, (build systems, package registries, or CI/CD serving widely-used libraries or services) with demonstrated Principal-level scope: setting technical direction across multiple teams, not just owning a single system.\n \n Direct experience standing up or significantly extending platform support for a language ecosystem- i.e. you've done the \"onboard a new toolchain/packaging model into an existing platform\" problem before, ideally including .NET (NuGet), Go (modules), or Rust (Cargo).\n \n Strong proficiency in Go, with the judgment to know when a new ecosystem's idioms should bend the plat","salary_min":229000,"salary_max":258000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"principal","tags":["pytorch","data-pipeline","agents","tensorflow"],"apply_url":"https://job-boards.greenhouse.io/chainguard/jobs/4698956006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-12T14:20:20Z","expires_at":"2026-09-29T13:48:54.065007Z","created_at":"2026-08-25T18:33:26.824395Z","updated_at":"2026-08-30T13:48:54.198028Z","company_name":"Chainguard","company_slug":"chainguard","company_logo_url":"https://www.google.com/s2/favicons?domain=chainguard.dev\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/94b0d6ed-331e-4eaf-97b4-93754391e8c4"},{"id":"fe3fba50-1c9f-4b22-82ec-ae5b67e070fa","company_id":"5fac52d7-9b0b-4990-80a2-e2949dd0af1d","title":"Software Engineer II, Integrations","slug":"software-engineer-ii-integrations-3e9f2081","description":"Attentive® is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. We’re the only marketing platform that combines powerful technology with human expertise to build authentic customer relationships. By unifying SMS, RCS, email, and push notifications, our AI-powered personalization engine delivers bespoke experiences that drive performance, revenue, and loyalty through real-time behavioral insights.\n  \n Recognized as the #1 provider in SMS Marketing by G2, Attentive partners with more than 8,000 customers across 70+ industries. Leading global brands like Crate and Barrel, Urban Outfitters, and Carter’s work with us to enable billions of interactions that power tens of billions in revenue for our customers.\n  \n With a distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney, Attentive’s team has been consistently recognized for its performance and culture. We’re proud to be included in  Deloitte’s Fast 500  (four years running!),  LinkedIn’s Top Startups ,  Forbes’ Cloud 100 (five years running!),  Inc.’s Best Workplaces , and the  Human Rights Campaign Foundation's Corporate Equality Index !\n About the Role \n The Integrations Experiences team develops features that help Attentive's customers work with the data they send into and out of Attentive. We deliver customer-facing observability tooling, our Integrations Marketplace, onboarding experiences, and capabilities that help marketers grow their audiences through continuous investment in creative tooling and AI-powered optimization.\n As a Software Engineer, you'll build full-stack experiences that make complex data workflows intuitive and actionable for customers. You'll design modern React applications and develop backend services that power Attentive's customer-facing products. Working closely with product managers, designers, and engineers, you'll shape features from concept to production, balancing user experience, performance, and scalability.\n What You’ll Accomplish \n \n Develop and maintain intuitive, reusable, and user-friendly web interfaces backed by scalable backend systems and APIs.\n Implement and optimize systems to enable customer observability into Attentive’s event-based platform\n Collaborate with cross-functional teams, product, and design to build applications that support communication channels for marketers\n Improve code quality through code reviews, testing, and advocating for best practices\n Identify and address technical debt to ensure the long-term health of our codebase\n Contribute to technical decisions and stay current with emerging technologies to enhance our product\n \n Your Expertise \n \n 3+ years of professional experience in software development focusing on frontend systems\n Strong proficiency with React and TypeScript, including modern frontend development patterns, performance optimization, and responsive UI development. Exposure to backend technologies such as Java, Kotlin and Spring Boot is a plus.\n Experience building and maintaining scalable, customer-facing, high-performance applications\n You have development experience with databases such as MySQL or PostgreSQL\n Experience leveraging agentic AI coding tools to accelerate software development while exercising strong engineering judgment.\n Proven ability to collaborate effectively with cross-functional teams\n Solid understanding of software development best practices, including code reviews, writing tests, and continuous integration\n Experience with testing frameworks such as React Testing Library and Playwright.\n You are excited by new technologies but are conscious of choosing them for the right reasons\n Curiosity, ownership, and a passion for delivering high-quality, user-friendly software.\n \n What We Use \n \n Our frontend is built with React and TypeScript, paired with technologies like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright\n Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS\n Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS\n Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm\n Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas\n \n You'll get competitive  perks and benefits , from health \u0026 wellness to equity, to help you bring your best self to work.\n For US based applicants: \n \n The US base salary range for this full-time position is $135,000 - $170,000 annually   + equity + benefits\n Our salary ranges are determined by role, level and location\n \n #LI-MN1 \n By applying for this position, your data will be processed as per Attentive's Privacy Policy . \n Attentive Company Values \n Default to Action - Move swiftly and with purpose\n Be One Unstoppable Team - Rally as each oth","salary_min":135000,"salary_max":170000,"location":"United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["pytorch","microservices","tensorflow","agents","api-design"],"apply_url":"https://job-boards.greenhouse.io/attentive/jobs/4363395009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-11T18:21:16Z","expires_at":"2026-09-29T13:49:12.195475Z","created_at":"2026-08-25T18:33:37.368996Z","updated_at":"2026-08-30T13:49:12.323395Z","company_name":"Attentive","company_slug":"attentive","company_logo_url":"https://www.google.com/s2/favicons?domain=attentive.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fe3fba50-1c9f-4b22-82ec-ae5b67e070fa"},{"id":"4b6dd3fa-7bf0-45bb-9581-df7e0937c37f","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"ML Engineer, Foundation Model Recipes","slug":"ml-engineer-foundation-model-recipes-fd25e6f7","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.\n In this hybrid role, you will report to a Senior Research Scientist.\n You will: \n \n Develop and extend cutting-edge research in robotics and machine learning to advance state-of-the-art recipes for advancing the quality, safety, and realism of embodied AI agents\n Partner within and across organizations to land disruptive and innovative tech in production\n Work with a variety of state-of-the-art Foundation Models \n Drive model development via data, eval, and systems\n Implement and extend large large scale data and evaluation pipeline\n \n You have: \n \n Masters degree in Computer Science, Machine Learning, Robotics, similar technical field of study, or equivalent practical experience\n Proficiency in Python\n Familiarity with one of the modern deep learning frameworks (e.g. Pytorch, JAX, Tensorflow)\n Prior work in an industrial or research setting developing recipes for ML models\n \n We prefer: \n \n Track record of publications in top-tier conferences or leading open source projects in the related fields\n Strong hands-on SWE skills, able to design, implement, and extend large distributed pipelines\n Experience in AV planning and related research\n Experience in labeling and curating data for ML eval and training\n \n  \n In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:\n Health, dental, vision, life, disability insurance Retirement Benefits: 401(k) with company match Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks Baby Bonding Leave: 18 weeks Holidays: 13 paid days per year \n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $175,000 — $215,000 USD","salary_min":175000,"salary_max":215000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["deep-learning","tensorflow","reinforcement-learning","autonomous-vehicles","agents","generative-ai","pytorch","robotics"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8109035","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-10T14:40:16Z","expires_at":"2026-09-29T13:35:05.036552Z","created_at":"2026-08-25T18:27:25.761878Z","updated_at":"2026-08-30T13:35:05.172268Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4b6dd3fa-7bf0-45bb-9581-df7e0937c37f"},{"id":"fddb1d0b-6927-4c25-ab63-444154aedc6f","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Staff ML Engineer, Perception Research","slug":"staff-ml-engineer-perception-research-0c8c4e3b","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation. \n This role follows a hybrid work schedule and reports to a Principal Research Scientist.\n You will :\n \n Conduct comprehensive experimentation to train and deploy state-of-the-art Multimodal LLMs and World models to perform 3D Perception using sensor information from Camera, LiDAR and Radar..\n Partner effectively with engineering and research teams across Waymo to deploy new models, and implement efficient workflows for model development and continuous training on new front-filled data.\n Apply and develop techniques such as quantization, pruning, knowledge distillation, and efficient attention mechanisms.\n Develop and maintain scalable data pipelines for Training \u0026 Eval to process data from multiple sources.\n Design and implement evaluation frameworks for perception models.\n Develop infrastructure for large-scale model distillation and bulk-inference pipelines for teacher models.\n Experiment with different model partitioning and sharding strategies to improve scalability and efficiency.\n Build and maintain tools for performance analysis, profiling (e.g., xprof), and debugging of ML models.\n \n You have: \n \n PhD or Masters in Computer Science, Machine Learning, Robotics, or a similar technical field, with 4+ years of industry or post-doc research experience in Reinforcement Learning or Foundation Models. \n Proficiency in implementing model training flows in a scalable, distributed and performant manner such as Data parallel, FSDP and other sharding approaches. \n Proficiency in JAX, Flax, and potentially TensorFlow/PyTorch.\n A willingness to work with complexity of globally distributed inference infrastructure.\n Hands on experience with optimizing the training and inference of Transformer architectures\n \n We prefer: \n \n PhD in Computer Science, Machine Learning, or Robotics, with a research focus on Reinforcement Learning, Foundation Models, or Multi-Modal learning.\n Substantial involvement in and contributions to high impact industry AI projects.\n Experience in generative models for domains such as world models, images, videos, 3D, using techniques such as diffusion or autoregressive models.\n Experience contributing to frameworks and libraries that improve training speed and scalability (e.g., JAX, Gemax, XManager)\n \n Disclosure for WA Based \u0026 Remote Roles: \n In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:\n Health, dental, vision, life, disability insurance Retirement Benefits: 401(k) with company match Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks Baby Bonding Leave: 18 weeks Holidays: 13 paid days per year\n  \n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $251,000 — $310,000 USD","salary_min":251000,"salary_max":310000,"location":"Mountain View, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["generative-ai","autonomous-vehicles","reinforcement-learning","data-pipeline","llm","pytorch","tensorflow","robotics"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8113233","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-07T23:27:50Z","expires_at":"2026-09-29T13:35:10.854883Z","created_at":"2026-08-25T18:27:25.997945Z","updated_at":"2026-08-30T13:35:10.989578Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fddb1d0b-6927-4c25-ab63-444154aedc6f"},{"id":"e0939c25-2c0e-4cd1-b5fd-76eb278483f6","company_id":"5fac52d7-9b0b-4990-80a2-e2949dd0af1d","title":"Senior Software Engineer, Intelligent Messaging, AI Journeys","slug":"senior-software-engineer-intelligent-messaging-ai-journeys-87ef0645","description":"Attentive® is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. We’re the only marketing platform that combines powerful technology with human expertise to build authentic customer relationships. By unifying SMS, RCS, email, and push notifications, our AI-powered personalization engine delivers bespoke experiences that drive performance, revenue, and loyalty through real-time behavioral insights.\n  \n Recognized as the #1 provider in SMS Marketing by G2, Attentive partners with more than 8,000 customers across 70+ industries. Leading global brands like Crate and Barrel, Urban Outfitters, and Carter’s work with us to enable billions of interactions that power tens of billions in revenue for our customers.\n  \n With a distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney, Attentive’s team has been consistently recognized for its performance and culture. We’re proud to be included in  Deloitte’s Fast 500  (four years running!),  LinkedIn’s Top Startups ,  Forbes’ Cloud 100 (five years running!),  Inc.’s Best Workplaces , and the  Human Rights Campaign Foundation's Corporate Equality Index !\n About the Role \n Our Engineering team creates innovative product experiences that power personalized marketing at massive scale. We develop cutting-edge applications and systems that process 100s of billions of messages and events per year, enabling marketers to connect effectively with hundreds of millions of consumers. Joining our team offers a high-growth career opportunity to work with some of the world’s most talented engineers in a high-performance and high-impact culture.\n As a Senior Software Engineer in our Intelligent Messaging, you will pioneer the future of personalized 1:1 marketing by architecting robust, scalable backend systems powered by advanced AI and LLMs, including cutting-edge Generative AI and GPT technologies. Collaborating with top-tier engineers, data scientists, product managers, and designers, you’ll craft the foundation and reshape the platform of multi-channel messaging experimentation to support innovative, AI-driven applications that empower marketers to forge deep, meaningful connections with consumers at scale. Your impactful work will drive the delivery of billions of tailored messages, transforming consumer shopping experiences and fueling success for the world’s leading brands.\n What You’ll Accomplish \n \n Develop and maintain scalable backend systems for our customer-facing products, ensuring high performance and reliability.\n Collaborate with cross-functional teams to build applications that support multi-channel communications for marketers.\n Implement and optimize systems that process and deliver billions of messages daily.\n Improve code quality through code reviews, testing, and advocating for best practices.\n Identify and address technical debt to ensure the long-term health of our codebase.\n Drive architectural design and technical decisions, and stay current with emerging technologies to enhance our products.\n \n Your Expertise \n \n 5+ years of professional experience in software development focusing on backend systems.\n Proficiency in Java, Python, or Go, with a strong understanding of object-oriented programming.\n Experience building and maintaining scalable, high-performance applications.\n Proven ability to collaborate effectively with cross-functional teams.\n Solid understanding of software development best practices, including code reviews, writing tests, and continuous integration.\n \n Nice to Haves \n \n Experience with service-oriented architecture and distributed systems.\n Familiarity with AWS services and cloud infrastructure.\n Knowledge of databases such as DynamoDB, Postgres, or Redis.\n Experience with messaging systems or streaming platforms (e.g., Kafka, Pulsar).\n Familiarity with frontend development with React and TypeScript.\n Experience with DevOps practices and tools such as Docker and Kubernetes.\n \n What We Use \n \n Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS.\n Infrastructure tooling includes Istio, Datadog,Terraform, CloudFlare, and Helm.\n Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS.\n Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and PlaywrightOur automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas.\n \n You'll get competitive  perks and benefits , from health \u0026 wellness to equity, to help you bring your best self to work.\n For US based applicants: \n \n The US base salary range for this full-time position is $190,000 - $230,000 annually   + equity + benefits\n Our salary ranges are determined by role, level ","salary_min":190000,"salary_max":230000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["microservices","api-design","cloud","llm","generative-ai","tensorflow","distributed-systems","pytorch"],"apply_url":"https://job-boards.greenhouse.io/attentive/jobs/4355309009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-05T22:34:53Z","expires_at":"2026-09-29T13:49:11.816919Z","created_at":"2026-08-25T18:33:37.346544Z","updated_at":"2026-08-30T13:49:11.951971Z","company_name":"Attentive","company_slug":"attentive","company_logo_url":"https://www.google.com/s2/favicons?domain=attentive.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e0939c25-2c0e-4cd1-b5fd-76eb278483f6"},{"id":"83d650f4-9869-405c-83a1-e9cf3b226d45","company_id":"f36ec848-cb19-4b95-a680-6733e58086c0","title":"Lead Machine Learning Engineer - Localization","slug":"lead-machine-learning-engineer-localization-dd7aa387","description":"May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology that literally reimagines the way AVs think. Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We’re building the world’s best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we’ve given more than 500,000 autonomous rides to real people around the globe. And we’re just getting started. We’re hiring people who share our passion for building the future, today, solving real-world problems and seeing the impact of their work. Join us. \n Job Summary \n The Autonomy Mapping \u0026 Localization group builds the spatial intelligence, semantic and topological mapping, and state estimation that let our autonomous vehicles understand where they are and what the world looks like, and we scale that technology safely and reliably to commercial operations serving riders and consumers. We are looking for a Lead ML Engineer to join our team and architect the next generation of our localization stack. As the Lead ML Engineer for Localization, you will build the production-grade feature extraction and state estimation that lets our autonomous vehicles precisely navigate the world's most challenging roads at scale.\n Essential Responsibilities \n \n Architect and drive the technical roadmap for a production-grade localization machine learning stack, spanning map and sparse landmark-based localization (vision/LiDAR/radar), optimized for real-time performance, robustness against sensor degradation, and integration with the broader autonomy system across diverse Operational Design Domains (ODDs).\n Lead the research, design, training, and validation of advanced neural architectures. This includes object detection, classification, segmentation, tracking, depth estimation, and 3D reconstruction to extract and model localization features (e.g., traffic signs, pole-like objects, keypoints, edges, signals, and road markings), for robust localization.\n Drive major feature development from inception to deployment. This includes high-level architecture design, rigorous code reviews, automated testing, mentorship of junior engineers, and technical resolution.\n Own the end-to-end data strategy for the localization feature extraction domain. You will define data curation, auto-labeling, synthetic data, and active learning pipelines to capture and resolve long-tail scenarios.\n Develop robust metrics and evaluation frameworks for localization performance, including feature extraction accuracy, temporal consistency, and system-level reliability across diverse ODDs.\n Define and validate failure mode and degradation criteria for localization features across ODDs, ensuring safety case coverage and graceful fallback behavior under sensor or model failure.\n Evaluate, adapt, and integrate frontier techniques, including multimodal localization and vision/fusion foundation models, translating research advances into production-ready solutions.\n Drive cross-functional alignment, translating complex autonomy goals into clear software and system requirements.\n \n Qualifications and Experience \n Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:\n Required \n \n Ph.D. or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field with a strong mathematical and engineering foundation.\n 7+ years of industry experience developing and deploying ML/DL models for computer vision or localization at scale.\n Deep expertise in several of the following areas:\n \n Computer Vision Foundations: Object detection, classification, segmentation, tracking, depth estimation, 3D reconstruction, and feature detection/description (e.g., SIFT, ORB, SuperPoint).\n Vectorized landmark and feature detection networks, BEV-based scene representation, and temporal modeling.\n Self-supervised/semi-supervised learning, open-vocabulary detection, and vision/fusion Foundation Models.\n \n Experience with feature extraction and/or fusion from imagery, LiDAR, and/or radar.\n Expertise in ML/DL development using PyTorch or TensorFlow, including experience with synthetic data generation, large-scale dataset handling, data curation, and active learning strategies.\n Strong programming skills in Python and/or C++ with experience in modular software design and Linux-based development.\n Expertise in ML optimization for real-time products with limited compute, such as quantization and pruning of large transformer models.\n Proven leadership in developing te","salary_min":235000,"salary_max":285000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["healthcare","generative-ai","robotics","autonomous-vehicles","tensorflow","computer-graphics","pytorch","computer-vision"],"apply_url":"https://job-boards.greenhouse.io/maymobility/jobs/8502300002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-04T17:26:06Z","expires_at":"2026-09-29T13:47:53.555408Z","created_at":"2026-08-25T18:33:06.971325Z","updated_at":"2026-08-30T13:47:53.684868Z","company_name":"May Mobility","company_slug":"may-mobility","company_logo_url":"https://www.google.com/s2/favicons?domain=maymobility.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/83d650f4-9869-405c-83a1-e9cf3b226d45"}],"page":1,"per_page":20,"total":392,"total_is_exact":true,"total_pages":20}