{"access":{"advertiser_pricing_url":"https://aidevboard.com/pricing","catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. API keys are optional for stable agent identity and keyed hourly throttling.","docs_url":"https://aidevboard.com/docs","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"9cf703e4-28cb-47a7-9151-d26f9745f43d","company_id":"74257563-5513-4a8d-a0f7-01f00c59aed6","title":"Senior Machine Learning Engineer, Relevance and Personalization (Query Intelligence)","slug":"senior-machine-learning-engineer-relevance-and-personalization-query-intelligence-b6fdeb9a","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 The Relevance and Personalization team at Airbnb is responsible for search and recommendation across the entire Airbnb digital platform. In this role you'll focus on query intelligence, the front door of search working on critical, impactful projects that turn what a guest types, taps, or says into a precise understanding of their intent, spanning autocomplete and smart compose, query tagging, query expansion, and intent modeling across Stays, Experiences, and Services.\n The Difference You Will Make: \n Query understanding is where every search begins, and it directly shapes retrieval, ranking, and ultimately the perfect match between guests and hosts. We build cutting-edge AI technologies across the end-to-end search ranking product stack w.r.t. data pipelines, feature and model innovations, serving and experimentation efficiency, leveraging rich signals from various types of data (structured, sequential, image, text, etc) and increasingly large language models at Airbnb. You'll build the models that parse free-form and natural-language multimodal queries, extract entities and location context, classify intent, and anticipate what guests want before they finish typing. We collaborate closely with teams across Airbnb to develop the ranking solutions and support a healthy marketplace for hosts and guests to further Airbnb's mission of creating a world where people can Belong Anywhere. Some past publications from the team can be found here: https://sites.google.com/view/airbnb-relevance-publications/home \n A Typical Day:  \n \n Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases, with a focus on query understanding.\n Develop query understanding capabilities — autocomplete and smart compose, query tagging (sequence tagging / NER), query expansion, and query/user intent modeling — and natural-language (\"search in your own words\") search experiences powered by modern NLP and LLMs.\n Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact.\n Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.\n Leverage third-party and in-house Machine Learning tools \u0026 infrastructure to develop reusable, highly differentiating and high-performing Machine Learning systems, enable fast model development, low-latency serving and ease of model quality upkeep.\n Example projects include: smart compose and language generation for search, LLM-based sequence taggers, LLM-driven query/location expansion, intent classification, and user-intent sequence modeling.\n \n Your Expertise: \n \n 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields.\n Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills.\n Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. neural networks/deep learning, optimization) and domains (eg. natural language processing, personalization, search and recommendation, marketplace optimization).\n Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive).\n Industry experience building end-to-end Machine Learning models.\n Experience applying large language models and modern NLP — e.g., sequence tagging/NER, text generation, intent classification, or embedding/representation learning.\n Familiarity with building natural-language, AI-native and agentic search experiences is a plus.\n Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).\n \n Your Location: \n This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your po","salary_min":200000,"salary_max":235000,"location":"United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","generative-ai","data-pipeline","agents","search","nlp","pytorch","tensorflow"],"apply_url":"https://careers.airbnb.com/positions/8065789?gh_jid=8065789","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T23:54:51Z","expires_at":"2026-08-14T14:11:22.875202Z","created_at":"2026-07-15T14:11:23.002744Z","updated_at":"2026-07-15T14:11:23.002744Z","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/9cf703e4-28cb-47a7-9151-d26f9745f43d"},{"id":"e6cf414e-5202-4a66-9735-43bcbeb83352","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Senior Machine Learning Engineer, Ads Content Understanding","slug":"senior-machine-learning-engineer-ads-content-understanding-06e45727","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 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .\n Reddit has a flexible workforce!  If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence.\n Ads Content Understanding (ACU) owns and produces signals that describe what Reddit content is about, how brand safe and suitable it is, and what users are trying to accomplish in commercial conversations. ACU is responsible for:\n \n The Knowledge Graph (entities, brands, products, and relationships across Reddit and external sources).\n Content taxonomies such as IAB, Shopify Standard Product Taxonomy, IAS, and other commercial taxonomies used for targeting, safety, and marketplace dynamics.\n Opinion mining for ads use cases: sentiment, stance, commercial intent, and other qualitative attributes of conversations.\n Shopping / product understanding: detecting product entities, product categories, and product attributes in organic conversations and aligning them with shopping catalogs.\n Signals and tags registry: a unified, governed catalog of ACU signals that powers retrieval, ranking, safety, and insights across Ads Foundations and partner teams. \n \n We are looking for a Senior Machine Learning Engineer (IC4) who will act as a key contributor to the Content Understanding roadmap for the Monetization org.\n This is not a research scientist or pure DS role; success is defined by robust, shipped systems and monetization impact.  The ideal candidate is a pragmatic engineer with strong software engineering fundamentals and solid ML intuition—not a pure research scientist. This is an Applied MLE role, requiring someone who can evaluate when to leverage hosted LLMs versus custom models, help scale content understanding to new modalities (e.g., video), and drive practical ML solutions that deliver business impact. \n Responsibilities: \n \n Operate across the full ML lifecycle (problem framing, data, modeling, evaluation, deployment, monitoring, and oncall), designing scalable ML pipelines and championing responsible AI (bias, safety, explainability) for ACU’s models and signals in production.\n Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, design reviews, setting technical standards, and uplifting the team’s modeling and systems craft.\n Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices. \n Drive operational excellence for ACU’s ML systems by defining SLOs, alerting, and dashboards for key signals (coverage, latency, precision/recall, cost)\n Build and evolve content understanding capabilities for commercial conversations (e.g., reviews vs. recommendations vs. comparisons vs. Q\u0026A; sentiment and stance; product entities and categories) and operationalize them as robust signals that power contextual and shopping ads, auto-targeting, new formats, and insights products.\n Drive LLM and modern ML best practices within ACU: define when to prompt, finetune, or distill; design evaluation and safety harnesses; and lead at least one major distillation effort to replace external APIs with in-house models.\n \n Required Qualifications: \n \n 5+ years of relevant MLE experience delivering production ML systems (models + pipelines + serving) at scale, ideally in large-scale content understanding domains, or Ads. \n Demonstrated Senior-level technical leadership: has contributed to architecture decisions, standards, and design reviews in their immediate team\n Strong communication skills, with the ability to explain complex technical trade-offs to PMs, DSs, and other engineering teams, especially in ambiguous, cross-team problem spaces like Seekers/Searchers monetization. \n Some experience building and shipping NLP / Language models / content understanding models to production (e.g., classifiers, encoders, sequence or session models), with clear business outcomes (e.g., CTR/ROAS uplift, safety improvements). Experience with commercial or intent modeling is a strong plus.\n \n Preferred Qualifications: \n \n Practical experience using LLMs in production for labeling, evaluation, or distillation (e.g., LM-as-judge, prompt-based classifiers, LLM-generated labels distilled into smaller models), including managing quality, cost, and latency trade-offs.\n Significant experience with PyTorch, TensorFlow, or similar, and production-quality code in Python (and ideally one staticall","salary_min":216700,"salary_max":303400,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["nlp","healthcare","tensorflow","llm","pytorch","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/8008648","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T22:21:59Z","expires_at":"2026-08-14T14:10:37.134107Z","created_at":"2026-07-15T14:10:37.261524Z","updated_at":"2026-07-15T14:10:37.261524Z","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/e6cf414e-5202-4a66-9735-43bcbeb83352"},{"id":"3b5bd89e-dae1-44b9-a41a-2e1a729363f6","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Principal Scientist / Associate Director, Agentic AI Research for Materials Science","slug":"principal-scientist-associate-director-agentic-ai-research-for-materials-science-e225ff03","description":"Your Impact at LILA \n Own the technical direction for agentic AI systems applied to materials science at Lila. You will set and execute the roadmap for autonomous agents that plan, run, and interpret materials experiments, based on understanding of internal knowledge and state-of-the-art research work in public literature. Your work shifts materials research from human-paced iteration to machine-paced experimentation through scientific reasoning and understanding.\n This is a player-coach role on the PS AI team. You will lead a small group of scientists and engineers, set the bar for scientific rigor and engineering quality, and partner with diverse teams so that agentic systems land on real programs. You will own the trade-offs between research ambition and production reliability, and represent the agentic-AI direction to technical leadership.\n The work spans foundational research and applied delivery. You will publish where the science merits it, ship systems that materials teams depend on, and shape how Lila scales agentic capabilities across its materials portfolio.\n What You'll Be Building \n \n Roadmap and direction. Define and execute the agentic AI roadmap for materials science, including agentic frameworks and retrieval-augmented generation for understanding multi-modal research data from research literature and other data sources.\n Agent system architecture. Lead the design of agentic frameworks grounded in fundamental scientific understanding and the state of the art, and deliver end-to-end systems on real-world projects.\n Team leadership. Hire, mentor, and grow a small cross-functional team of scientists and engineers; set the bar for scientific rigor, code quality, and reproducibility.\n Cross-team partnership. Partner with diverse teams at Lila to push the state of the art and deliver systems that integrate with experimental infrastructure and land on real programs.\n Research currency and external voice. Track state-of-the-art in agentic AI, scientific ML, data extraction, and reasoning models; translate external advances into internal direction, and publish or present where the science merits it.\n \n What You'll Need to Succeed \n \n PhD in Computer Science, Machine Learning, Materials Science, Chemistry, Physics, or a related field, with 5+ years of post-PhD research and applied ML experience.\n Track record of building and shipping agentic systems, ML pipelines, or autonomous research workflows that delivered measurable scientific or product impact.\n Deep expertise across modern ML, NLP, and reasoning: LLMs, agentic frameworks, tool use, planning, data extraction, and multi-modal data.\n Working knowledge of materials science, computational chemistry, or condensed-matter physics sufficient to ground agent behavior in real scientific constraints.\n Proficiency in Python and the ML software stack, with strong engineering habits around reproducibility, testing, and production deployment.\n Experience leading scientists and engineers: setting technical direction, hiring, mentoring, and developing team members.\n Clear written and verbal communication; able to translate between research, engineering, and program stakeholders.\n \n Bonus Points For \n \n Publications, patents, or open-source contributions in agentic AI, scientific ML, or autonomous research systems.\n Experience integrating agents with real-world materials science tasks and familiarity with materials data representations and ontologies.\n Production experience with workflow orchestration and distributed compute on cloud or HPC.\n Community recognition: invited talks, conference organizing, or community leadership in agentic AI or scientific AI.\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $288,000 — $420,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.\n LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonom","salary_min":288000,"salary_max":420000,"location":"Boston, MA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["agents","rag","nlp","llm","research"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4273850009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T13:33:45Z","expires_at":"2026-08-14T14:20:39.311843Z","created_at":"2026-07-10T14:18:13.983856Z","updated_at":"2026-07-15T14:20:39.411647Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3b5bd89e-dae1-44b9-a41a-2e1a729363f6"},{"id":"53df0b7f-aa7f-4625-898a-170692e922fd","company_id":"19a78c6a-11dc-4d21-8273-0d2d2bad39b1","title":"Data Scientist II","slug":"data-scientist-ii-95683f8f","description":"Toast is driven by building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love.\n Toast is revolutionizing the way the restaurant industry does business by pairing technology with an extraordinary commitment to customer success. We help restaurants streamline operations, increase revenue, and deliver amazing guest experiences through our platform that combines restaurant point of sale, guest-facing technology, and award-winning customer support. Join us as we empower the restaurant community to delight guests, do what they love, and thrive.  This role is for a current vacancy.\n Bready* to make a change? \n The Toast AI Engineering team is seeking a Data Scientist to embed data science capabilities into the Toast platform by partnering with engineers and product managers to develop statistical and machine learning models that power key product lines.\n About this Roll* (Responsibilities) : \n \n Apply a diverse set of expertise including data mining, statistical analysis and machine learning to deliver impactful, objective, and actionable data insights that enable informed business and product decisions\n Collaborate with cross-functional teams, including sales, marketing, and product, to identify business opportunities and develop data-driven solutions that drive growth and engagement.\n Partner with line of business teams and collaborate with product managers, engineers and data scientists to foster data-driven decisions that yield significant impacts \n Able to effectively communicate analysis, insights and recommendations to high-level business partners in verbal, visual and written formats\n Thrive in a dynamic and rapidly evolving environment\n \n Do you have the right ingredients* (Requirements) ? \n \n Bachelors in computer science, engineering, math, statistics, economics, or other quantitative discipline; Masters preferred.\n 2+ years of data science experience in an industry environment.\n Have solid statistical and machine learning foundations. Familiar with machine learning concepts (e.g. regression/classification, clustering, offline/online model evaluation). \n Experience with advanced machine learning techniques, including supervised and unsupervised learning, graph algorithms, deep learning (e.g., NLP), recommendation systems, and generative AI.\n Experience with Python and SQL, and ML frameworks (e.g. scikit-learn, Tensorflow, PyTorch)\n Experience with cloud solutions, preferably with AWS tooling (e.g. SageMaker, DynamoDB, Athena, Glue, etc.)\n Experience with model workflow orchestration tool (e.g. Airflow)\n Experience collaborating with engineers, product managers, and other cross-functional teams\n Excellent verbal and written communication skills\n Ability to communicate sophisticated quantitative analysis in a clear, precise, and actionable manner.\n \n Special Sauce* (Nice to Haves):  \n \n Experience working on LLM applications, including prompting, RAG, and evaluation.\n Experience in software engineering best practices and tools including object-oriented programming, test-driven development, CI/CD, git, shell scripting, task orchestration.\n Experience shipping machine learning systems in production environments.\n Experience in A/B testing and other experimentation methodologies for effective product launch measurement.\n \n  \n AI at Toast \n At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.\n Our Total Rewards Philosophy  We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at  https://careers.toasttab.com/toast-benefits .\n The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. \n Pay Range \n $110,000 — $136,000 CAD \n How Toast Uses AI in its Hiring Process \n Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are","salary_min":110000,"salary_max":136000,"location":"Canada","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["generative-ai","tensorflow","deep-learning","cloud","llm","nlp","pytorch","data-science"],"apply_url":"https://careers.toasttab.com/jobs?gh_jid=8052241","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T20:16:37Z","expires_at":"2026-08-14T14:11:49.3663Z","created_at":"2026-07-09T14:09:43.741168Z","updated_at":"2026-07-15T14:11:49.491623Z","company_name":"Toast","company_slug":"toast","company_logo_url":"https://www.google.com/s2/favicons?domain=pos.toasttab.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/53df0b7f-aa7f-4625-898a-170692e922fd"},{"id":"6e73bc75-a490-4b93-af2d-5d0040a7eb71","company_id":"6ea0f41a-b13e-481a-b410-5195f391f939","title":"Research Engineer, Post-Training Inference","slug":"research-engineer-post-training-inference-ff4ae18b","description":"About the role \n The Model Shaping team at Together AI works on products and research focused on tailoring open foundation models to downstream applications. We build services that enable machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad range of ideas across machine learning, natural language processing, and ML systems.\n As a Research Engineer within Model Shaping, you will develop a platform that enables users to customize open-source models with their own data. Working across the training and inference stacks, you will build and improve our Fine-Tuning, Reinforcement Learning, and Evaluation services – from ensuring a seamless path from post-training to production serving, to optimizing the inference engine for RL training workloads. You will collaborate closely with our product, research, and engineering teams to keep the API reliable, performant, and well integrated into the company's technical infrastructure. Above all, you will help build the foundational layer of the open-source AI ecosystem, enabling developers around the world to efficiently create high-quality models tailored to their specific applications.\n Responsibilities \n \n Design and build Together’s systems for customizing open-source models\n Build integrations between the Model Shaping and Inference platforms to ensure a seamless path from post-training to serving production workloads\n Add features to inference engines for large-scale post-training experiments, including optimizations for RL workloads\n Make sure the service is stable and robust, participating in an on-call rotation and ensuring 24/7 availability of our platform\n \n Requirements \n \n Have 2+ years of experience building and deploying machine learning-based services in a production environment\n Have hands-on experience with modern inference engines, such as SGLang, vLLM, and TensorRT-LLM\n Are familiar with the latest methods for fine-tuning LLMs and other AI models\n Have a strong software engineering background in Python or Go\n Stay up to date with the latest advances and trends in the machine learning community\n \n Experience in any of the following will make you stand out \n \n Serving low-precision (FP4/FP8) models, multiple LoRA adapters within one model instance (Multi-LoRA), or models distributed across several GPU nodes\n Optimizing the performance of RL training workloads\n Developing CUDA/Triton/CuTE DSL kernels for inference\n Developing large-scale and high-load production systems\n Maintaining or contributing to open-source ML projects\n Managing machine learning workloads on Kubernetes clusters\n \n About Together AI \n Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, ATLAS, RedPajama, and Mamba. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.\n Compensation \n We offer competitive compensation, startup equity, health insurance, and other benefits. The US base salary range for this full-time position is $200,000 - $290,000. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.\n Equal Opportunity \n Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.\n Please see our privacy policy at  https://www.together.ai/privacy","salary_min":200000,"salary_max":290000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["search","generative-ai","reinforcement-learning","nlp","llm","fine-tuning","gpu","research"],"apply_url":"https://job-boards.greenhouse.io/togetherai/jobs/5179372007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-06T18:21:40Z","expires_at":"2026-08-14T14:02:19.694954Z","created_at":"2026-07-09T14:02:08.323229Z","updated_at":"2026-07-15T14:02:19.81991Z","company_name":"Together AI","company_slug":"together-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=together.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6e73bc75-a490-4b93-af2d-5d0040a7eb71"},{"id":"37531681-5540-4d72-bae6-adb400a217ff","company_id":"f5ee7284-a657-4da2-b351-cb806a3681cd","title":"Member of Technical Staff","slug":"member-of-technical-staff-58cdf6b3","description":"SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.  Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. \n Member of Technical Staff (X.AI LLC; Palo Alto, CA): Introduce innovative techniques and analyses to theAI field to facilitate breakthroughs in quantitative reasoning and language understanding. Stabilize large language model training, pipeline parallelism training of large language models, and fine-tuning large language models with truthful data. Ensure organization’s work is aligned with broader company objectives. Spend time working on hands-on technical problems including design and implementation. Perform cutting-edge research on advanced techniques from AI and deep learning, including neural network architectures, language modeling, and speech recognition. Work closely with leaders across the company to deliver impactful projects which may involve work in areas such as machine learning, applied data science, recommendation systems, and information retrieval systems. Telecommuting permitted. Reference: 00100860  \n The position requires a Bachelor’s or foreign equivalent degree in Computer Science, Computer Engineering, Mechanical Engineering, Machine Learning or in a related field and 2 years of experience in the job offered or in a computer-related occupation.  \n Special Requirements: Position requires experience, knowledge or coursework in each of the following skills:\n \n BigData systems such as Spark, Hadoop, BigQuery, and related technology to build highly scalable data processing systems \n Building large-scale Kubernetes clusters for data storage, processing, and analysis on on-prem  systems and cloud computing \n Applied machine learning techniques and deploying large-scale deep learning systems 4. Working with distributed system engineers and AI researchers in developing technologies in the area of natural language processing, computer vision, and speech recognition applications 5. Rust, C++, or Python programming language to build tooling and features within company software development code and standards. \n Building applications with hardware accelerators, such as GPUs, TPUs from GCP, Azure, and AWS.Employment and background checks may be required. \n \n Salary: $324,000 - $396,000 per year \n To Apply: Any interested applicant may click on the APPLY NOW button above to apply for this position. \n SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice .","salary_min":324000,"salary_max":396000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","nlp","speech","computer-vision","search","deep-learning","fine-tuning","distributed-systems"],"apply_url":"https://job-boards.greenhouse.io/xai/jobs/5173208007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-24T19:28:53Z","expires_at":"2026-08-14T14:04:42.867245Z","created_at":"2026-06-28T14:03:13.307512Z","updated_at":"2026-07-15T14:04:43.003373Z","company_name":"xAI","company_slug":"xai","company_logo_url":"https://www.google.com/s2/favicons?domain=x.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/37531681-5540-4d72-bae6-adb400a217ff"},{"id":"dd43e8fb-8ef2-476d-b3d2-6ace126b3474","company_id":"f5ee7284-a657-4da2-b351-cb806a3681cd","title":"Member of Technical Staff","slug":"member-of-technical-staff-ea022ae5","description":"SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.  Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. \n Member of Technical Staff (X.AI LLC; Palo Alto, CA): Build collaborative relationships with the Principal and Staff engineering community as well as with engineering and product management leaders, and partner to deliver impact. Define the vision and strategy for the organization and have a substantial impact on the vision and strategy of customer and partner organizations. Plan and deliver projects that impact multiple organizations. Projects include models and large language model training, pipeline parallelism training of large language models, and fine tuning large language models with truthful data. Identify opportunities for technological differentiation, investment, or divestment. Ensure organization’s work is aligned with broader company objectives. Introduce innovative techniques and analyses to the AI field to facilitate breakthroughs in quantitative reasoning and language understanding. Provide mentorship and guidance to senior technical leaders and managers. Working on hands-on technical problems including design and implementation. Perform cutting-edge research on advanced techniques from AI and deep learning, including neural network architectures, language modeling, and speech recognition. Work closely with leaders across the company to deliver impactful projects which may involve work in areas such as machine learning, applied data science, recommendation systems, and information retrieval systems. Reference: 00101156. \n Minimum requirements: \n \n Must have a Bachelor’s degree in Computer Science, Artificial Intelligence, MachineLearning, Information Technology, or a related field, plus 5 years of progressive post-baccalaureate experience in AI/ML research or development. \n Alternatively, employer will accept a Master’s degree in Computer Science, Artificial Intelligence, Machine  Learning, Information Technology or a related field, plus 3 years of experience in AI/ML research or  development. \n Must have 3 years of experience in each of the following: \n Developing and applying AI models, including large language models, neural networks, or  reinforcement learning. \n Experience in Python and other relevant languages (such as C++, Java), using ML frameworks (such as PyTorch, TensorFlow, or JAX). \n Assessing system performance and designing scalable, efficient solutions for inference and model  deployment. \n Optimizing computational efficiency and memory usage through advanced algorithmic techniques or quantization. \n Building and maintaining robust, high-availability infrastructure for AI/ML services. ∙ Collaborating with cross-functional teams to define technical vision, strategy, and deliver impactful  projects. \n Mentoring and guiding senior technical leaders and managers in hands-on technical problem solving.∙ Driving innovation by introducing new techniques and analyses to advance AI capabilities in  quantitative reasoning and language understanding. \n Leading efforts in resource management, automation, and orchestration for large-scale ML  infrastructure. \n \n Salary: $324,000 - $396,000 per year \n To Apply: Any interested applicant may click on the APPLY NOW button above to apply for this position. \n SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice .","salary_min":324000,"salary_max":396000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["pytorch","tensorflow","nlp","deep-learning","speech","llm","reinforcement-learning","fine-tuning"],"apply_url":"https://job-boards.greenhouse.io/xai/jobs/5173142007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-24T19:05:16Z","expires_at":"2026-08-14T14:04:42.68898Z","created_at":"2026-06-28T14:03:13.39564Z","updated_at":"2026-07-15T14:04:42.829436Z","company_name":"xAI","company_slug":"xai","company_logo_url":"https://www.google.com/s2/favicons?domain=x.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/dd43e8fb-8ef2-476d-b3d2-6ace126b3474"},{"id":"62cbc23f-7693-467d-ba4e-9650055ac812","company_id":"12105b3e-eb1d-4a92-95b6-855042facaf1","title":"Applied Scientist II","slug":"applied-scientist-ii-d06185c2","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  \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 lif","salary_min":167500,"salary_max":220000,"location":"Seattle, WA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["deep-learning","agents","nlp","reinforcement-learning","pytorch","computer-vision","llm","tensorflow"],"apply_url":"https://www.qualtrics.com/careers/us/en/job/8017422?gh_jid=8017422","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-22T23:55:49Z","expires_at":"2026-08-14T14:21:25.729584Z","created_at":"2026-06-28T14:18:02.43735Z","updated_at":"2026-07-15T14:21:25.823318Z","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/62cbc23f-7693-467d-ba4e-9650055ac812"},{"id":"9583cad2-c741-4058-8739-a27068aa40a4","company_id":"b467c425-56b3-40ce-826a-e603e82a08bd","title":"Distinguished Machine Learning Engineer - Safety","slug":"distinguished-machine-learning-engineer-safety-81973176","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 Distinguished Machine Learning Engineer/Technical Director in the Safety organization at Roblox, you will drive the overall technical vision and execution for all machine learning initiatives focused on maintaining the safety and civility of our users. Our industry-leading safety features ensure Roblox remains a safe and inclusive environment for our community to express themselves creatively and share experiences without fear. The Safety org is the reason why Roblox is the safest place on the internet, protecting users You will provide technical leadership on AI/ML efforts for Trust and Safety as the Roblox platform scales to serve different age groups and geographic locations.\n You Will:\n \n Own the technical direction and implementation of machine learning solutions for safety-related systems\n Lead and mentor other engineers, fostering a culture of technical excellence and inclusivity\n Break down long-term product requirements into iterative deliverable stages, ensuring continuous improvement\n Craft and build large-scale machine learning models with billions of parameters, ensuring production-readiness\n Facilitate challenging technical decisions across multiple teams, demonstrating empathy and finding common understanding\n Collaborate with cross-functional teams to define and prioritize the machine learning roadmap\n \n You Have:\n \n 10+ years of experience delivering and improving large-scale machine learning systems\n Proven expertise in creating and launching machine learning models from scratch\n Ability to handle data problems, train models with large datasets, and ensure system reliability at scale\n Experience with distributed systems, data architecture, and model extraction\n Strong programming skills and willingness to be hands-on as necessary\n Prior experience in a leadership role with a technical focus, including mentoring engineering teams\n \n You Are:\n \n A creative and strategic problem-solver, able to simplify complex issues while integrating fresh ideas\n Committed to fostering a diverse and inclusive workplace where everyone feels valued and supported\n Passionate about maintaining deep technical expertise while meeting end-user needs\n Knowledgeable about cutting-edge ML technologies, including LLMs\n Experienced in NLP or computer vision (preferred)\n Familiar with maintaining and evolving safety systems at scale (preferred)\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 $399,420 — $457,970 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":399420,"salary_max":457970,"location":"San Mateo, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["llm","nlp","computer-vision","distributed-systems","machine-learning"],"apply_url":"https://careers.roblox.com/jobs/7931911?gh_jid=7931911","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-18T00:37:56Z","expires_at":"2026-08-14T14:20:00.164414Z","created_at":"2026-06-28T14:16:42.442434Z","updated_at":"2026-07-15T14:20:00.258831Z","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/9583cad2-c741-4058-8739-a27068aa40a4"},{"id":"6f09fbcc-ed04-4755-82e5-c687ef25ec12","company_id":"26618e2f-35c7-42eb-8f60-bd25a7e9a0d2","title":"Senior Data Scientist, CX Analytics","slug":"senior-data-scientist-cx-analytics-f5afe4b1","description":"Ready to do the most impactful work of your career? At  Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for \"good enough,\" you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.”  learn more about working at Coinbase .\n As a Senior Data Scientist on the CX Consumer Analytics team, you will serve as the foundational link between CX operations and top-line financial impact, owning the revenue calibration models, experimentation frameworks, and behavioral intelligence that connect every customer support interaction to Coinbase's asset accumulation flywheel. You will partner closely with CX Analytics Engineers, Program Managers, and Product teams to translate complex operational and behavioral data into defensible, executive-ready insights that drive measurable improvements in retention, product adoption, and automation quality.\n What you'll do: \n \n Own and evolve CX's Downstream Impact of Support (DSI) revenue calibration models, translating support interaction data into quantified revenue signals.\n Design and execute causal inference frameworks and experiments to measure the incremental impact of CX programs (Concierge, Proactive Outreach, automation interventions) on customer retention and product engagement.\n Build and maintain LLM-powered classification pipelines for CX contact taxonomy, customer friction detection, and issue attribution, partnering with Analytics Engineers to productionize models into CX's governed Source of Truth infrastructure.\n Partner with CX Program Managers and Product teams to define segmentation models and behavioral signals that enable personalized experiences and improve business outcomes.\n Maintain a high bar for statistical rigor across CX's analytics function, ensuring experimentation, causal analyses, and model outputs meet the standards required for executive reporting and regulatory defensibility.\n \n Required Skills and Experience: \n \n A BA/BS in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics) with 5+ years of relevant experience, or a PhD in a quantitative field with 3+ years of relevant experience.\n Demonstrated experience building revenue attribution or causal impact models and driving data science projects through ambiguous problem spaces in a consumer-facing or operational analytics context.\n Practical expertise applying statistical concepts including A/B testing, causal inference, and ML to real-world business problems, with a high bar for production-grade accuracy and evaluation rigor.\n Experience designing and deploying LLM-based classification or NLP pipelines for operational or customer-facing use cases.\n Ability to influence cross-functional stakeholders by synthesizing complex model outputs into clear, actionable narratives for executive and product audiences.\n Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human‑in‑the‑loop practices to deliver business‑ready outputs and drive measurable improvements in efficiency, cost, and quality.\n Pay Transparency Notice: Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)). \n  \n Annual base salary range (excluding equity and bonus):\n $180,370 — $212,000 USD \n \n Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.\n Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws. \n US Applicants: View Employee Rights , Know Your Rights , and E-Verify Notice of Participation. \n Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial . \n Data Privacy \u0026 Arbitration: By submitting your application, you agree to our Candidate Privacy Notice . US applicants: By submitting your application, you agree to Arbitration of Disputes .","salary_min":180370,"salary_max":212000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["nlp","llm","generative-ai","code-generation","data-science"],"apply_url":"https://www.coinbase.com/careers/positions/8009392?gh_jid=8009392","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-16T15:12:04Z","expires_at":"2026-08-14T14:10:58.51767Z","created_at":"2026-06-28T14:08:51.452766Z","updated_at":"2026-07-15T14:10:58.653075Z","company_name":"Coinbase","company_slug":"coinbase","company_logo_url":"https://www.google.com/s2/favicons?domain=www.coinbase.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6f09fbcc-ed04-4755-82e5-c687ef25ec12"},{"id":"0c54aba6-872e-413a-9d2c-1b6a1a38767c","company_id":"053355fc-0162-4bb9-b414-cbf7679ee9c8","title":"Director, Research - Frontier Benchmarks","slug":"director-research-frontier-benchmarks-d2ef3009","description":"About Snorkel \n At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.\n We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!\n ABOUT THE ROLE  \n We’re looking for a Director to lead a team of researchers designing the datasets that define and advance the frontier of AI. This team sits at the intersection of research, product strategy, and go-to-market. You and the team will collaborate with academic partners, work with researchers at frontier labs, and utilize internal tools for evaluation and error analysis to identify the data, skills and capabilities that will improve model performance. You will uncover gaps in current frontier models and design a wide variety of RL and domain specific benchmarks.  \n  \n MAIN RESPONSIBILITIES  \n \n Define the process and decide what data we build next by combining market signal from customers and GTM with your team’s read on where frontier labs are headed.\n Define and own the quality for benchmark design and support GTM in positioning it against existing datasets.\n Mentor and grow a technical team comfortable with x-functional and customer- facing work, setting a high standard for quality and velocity while staying hands-on yourself. \n Foster external and academic collaborations related to our areas of interest \n Stay at the frontier: Track new benchmarks, agentic evaluation, and RL training research and tie back to the dataset portfolio we focus on \n \n  \n PREFERRED QUALIFICATIONS  \n \n 8+ years in applied AI, ML, or research roles, including experience leading or mentoring senior researchers\n Previous experience building benchmarks and doing data-centric research\n Experience setting the roadmap and vision for teams and collaborating frequently with the executive team\n Proven ability to operate cross-functionally  and thrive in fast-paced, ambiguous environments while managing competing priorities\n Experience and interest in being customer-facing and translating technical contributions to business impact \n Ph.D. in machine learning, NLP, or a related field preferred; equivalent industry or research lab experience considered.\n Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location.\n Salary range(s) for this role\n $325,000 — $450,000 USD \n Be Your Best at Snorkel \n Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.\n Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of 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 law. All employment is decided on the basis of qualifications, performance, merit, and business need. \n We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.","salary_min":325000,"salary_max":450000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["generative-ai","nlp","agents","research"],"apply_url":"https://job-boards.greenhouse.io/snorkelai/jobs/6035518004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-15T22:41:52Z","expires_at":"2026-08-14T14:04:52.890918Z","created_at":"2026-06-28T14:03:22.108116Z","updated_at":"2026-07-15T14:04:53.083679Z","company_name":"Snorkel AI","company_slug":"snorkel-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=snorkel.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0c54aba6-872e-413a-9d2c-1b6a1a38767c"},{"id":"7dd74875-e6d5-4dd6-a098-d5e3a852c9d3","company_id":"19a78c6a-11dc-4d21-8273-0d2d2bad39b1","title":"Data Scientist II","slug":"data-scientist-ii-15025958","description":"Toast is driven by building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love.\n Toast is revolutionizing the way the restaurant industry does business by pairing technology with an extraordinary commitment to customer success. We help restaurants streamline operations, increase revenue, and deliver amazing guest experiences through our platform that combines restaurant point of sale, guest-facing technology, and award-winning customer support. Join us as we empower the restaurant community to delight guests, do what they love, and thrive.\n Bready* to make a change? \n The Toast AI Engineering team is seeking a Data Scientist to embed data science capabilities into the Toast platform by partnering with engineers and product managers to develop statistical and machine learning models that power key product lines.\n About this Roll* (Responsibilities) : \n \n Apply a diverse set of expertise including data mining, statistical analysis and machine learning to deliver impactful, objective, and actionable data insights that enable informed business and product decisions\n Collaborate with cross-functional teams, including sales, marketing, and product, to identify business opportunities and develop data-driven solutions that drive growth and engagement.\n Partner with line of business teams and collaborate with product managers, engineers and data scientists to foster data-driven decisions that yield significant impacts \n Able to effectively communicate analysis, insights and recommendations to high-level business partners in verbal, visual and written formats\n Thrive in a dynamic and rapidly evolving environment\n \n Do you have the right ingredients* (Requirements) ? \n \n Bachelors in computer science, engineering, math, statistics, economics, or other quantitative discipline; Masters preferred.\n 2+ years of data science experience in an industry environment.\n Have solid statistical and machine learning foundations. Familiar with machine learning concepts (e.g. regression/classification, clustering, offline/online model evaluation). \n Experience with advanced machine learning techniques, including supervised and unsupervised learning, graph algorithms, deep learning (e.g., NLP), recommendation systems, and generative AI.\n Experience with Python and SQL, and ML frameworks (e.g. scikit-learn, Tensorflow, PyTorch)\n Experience with cloud solutions, preferably with AWS tooling (e.g. SageMaker, DynamoDB, Athena, Glue, etc.)\n Experience with model workflow orchestration tool (e.g. Airflow)\n Experience collaborating with engineers, product managers, and other cross-functional teams\n Excellent verbal and written communication skills\n Ability to communicate sophisticated quantitative analysis in a clear, precise, and actionable manner.\n \n Special Sauce* (Nice to Haves):  \n \n Experience working on LLM applications, including prompting, RAG, and evaluation.\n Experience in software engineering best practices and tools including object-oriented programming, test-driven development, CI/CD, git, shell scripting, task orchestration.\n Experience shipping machine learning systems in production environments.\n Experience in A/B testing and other experimentation methodologies for effective product launch measurement.\n \n  \n AI at Toast \n At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.\n Our Total Rewards Philosophy  We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at  https://careers.toasttab.com/toast-benefits .\n The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. You can learn more about how we align pay with local labor markets in our Geographic Pay Zone Philosophy . \n Zone A\n $112,000 — $179,000 USD \n Zone B\n $97,000 — $155,000 USD \n Zone C\n $87,000 — $139,000 USD \n How Toast Uses AI in its Hiring Process \n Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-ta","salary_min":87000,"salary_max":139000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["pytorch","tensorflow","generative-ai","cloud","llm","nlp","deep-learning","data-science"],"apply_url":"https://careers.toasttab.com/jobs?gh_jid=7984730","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-12T20:12:26Z","expires_at":"2026-08-14T14:11:49.436344Z","created_at":"2026-07-03T14:09:36.870469Z","updated_at":"2026-07-15T14:11:49.562645Z","company_name":"Toast","company_slug":"toast","company_logo_url":"https://www.google.com/s2/favicons?domain=pos.toasttab.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7dd74875-e6d5-4dd6-a098-d5e3a852c9d3"},{"id":"f3eb479e-5552-4d76-a5b3-f7518973b636","company_id":"168d43fe-0922-420c-9743-59e0a899fd9d","title":"Research Engineer, Knowledge Graph Intelligence","slug":"research-engineer-knowledge-graph-intelligence-8f4b8bdf","description":"A Career with point72’s Surveillance team \n Point72’s Surveillance team sets the industry standard for intelligence-driven surveillance by proactively identifying, monitoring, and assessing various sources of compliance risk using proprietary tools and specialized tradecraft. We support senior management by providing strategic assessments, actionable recommendations, and real-time escalations. At Point72, members of the Surveillance team conduct integrated trade and communication surveillance and collaborate to turn information into intelligence for our internal customers. The team also monitors employee activity for evidence of violations of applicable federal securities laws, internal compliance policies and procedures, and relevant rules and regulations enforced by the SEC, FINRA, and other organizations.\n   \n What you’ll do \n As a Machine Learning Engineer - Applied Scientist you will play a critical role in developing algorithmic solutions and models for production-ready applications that support our front office investment professionals. You will specialize in natural language processing (NLP) solutions that extract insights from unstructured text data, with additional capabilities in predictive modeling, clustering, and time series analysis. You will manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. You will apply, adapt, and extend existing results in the broad field of NLP, while also conducting novel research as required. Specifically, you will:\n \n Contribute to projects across various machine learning (ML) disciplines, including NLP, unstructured data analysis, predictive modeling, and classic machine learning.\n Implement GenAI solutions, utilize ML infrastructure, and contribute to modeling, data preparation, optimization, and performance enhancements.\n Work with sparse data and apply techniques to improve model accuracy and generalization.\n Conduct data evaluation, including data preprocessing, feature engineering, and model performance assessment.\n Collaborate cross-functionally with data engineers, software developers, and product teams to integrate models into production systems.\n Stay up to date with the latest advancements in natural language processing and machine learning, applying new techniques as needed.\n \n   \n What’s REQUIRED \n \n PhD, master's degree, or 4+ years of CS, CE, ML or related field experience.\n 6+ years of experience building ML models and developing algorithms.\n Strong proficiency in Python, and hands-on experience with NumPy, Hugging Face, PyTorch, and spaCy for NLP applications.\n Prior experience in the domains of LLMs, foundation models, or large-scale deep learning systems, with a complete understanding of modern training, fine-tuning, quantization, and model evaluation.\n Expertise in working with sparse data and applying techniques such as data augmentation, weak supervision, and semi-supervised learning.\n Solid grasp of NLP concepts, including tokenization, embeddings, attention mechanisms, and transformer-based architectures.\n Experience with data evaluation techniques, model explainability, and error analysis.\n Experience working in a Linux environment.\n Commitment to the highest ethical standards.\n \n  \n We take care of our people \n We invest in our people, their careers, their health, and their well-being. When you work here, we provide:\n \n Fully-paid health care benefits\n Generous parental and family leave policies\n Volunteer opportunities\n Support for employee-led affinity groups representing women, people of color, and the LGBT+ community\n Mental and physical wellness programs\n Tuition assistance\n A 401(k) savings program with an employer match and more\n \n   \n  \n About Point72\n Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry's brightest talent by cultivating an investor-led culture and committing to our people's long-term growth. For more information, visit https://point72.com/.\n The annual base salary range for this role is $175,000-$250,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.","salary_min":175000,"salary_max":250000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["llm","fine-tuning","nlp","search","pytorch","generative-ai","deep-learning","research"],"apply_url":"https://boards.greenhouse.io/point72/jobs/8531773002?gh_jid=8531773002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-10T20:47:54Z","expires_at":"2026-08-14T14:14:35.45214Z","created_at":"2026-06-28T14:12:00.79685Z","updated_at":"2026-07-15T14:14:35.551893Z","company_name":"Point72","company_slug":"point72","company_logo_url":"https://www.google.com/s2/favicons?domain=point72.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f3eb479e-5552-4d76-a5b3-f7518973b636"},{"id":"fd2d788a-a2ca-4ecb-a331-1497714b42e6","company_id":"26618e2f-35c7-42eb-8f60-bd25a7e9a0d2","title":"Staff Machine Learning Engineer(Platform - Identity)","slug":"staff-machine-learning-engineerplatform-identity-1f63666a","description":"Ready to do the most impactful work of your career? At  Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for \"good enough,\" you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.”  learn more about working at Coinbase .\n Staff Machine Learning Engineer, Identity Verification\n As a Staff Machine Learning Engineer on the Identity Verification team within the Platform group, you'll own the ML systems that determine whether a person, document, and capture session are legitimate. Every signup, account recovery, and high-risk action at Coinbase depends on these models. You'll lead the technical strategy for IDV ML end-to-end, from architecture through production enforcement, protecting the integrity of millions of accounts.\n What you'll do: \n \n Own the full IDV ML stack, including document authenticity models, 1:1 and 1:N face-match, liveness detection, presentation-attack detection, and deepfake/injection detection from feature pipeline through threshold tuning and production enforcement.\n Build identity-graph systems using GNNs that cluster accounts sharing biometric, device, and document signals to detect synthetic-identity rings and coordinated fraud at onboarding.\n Develop behavioral and device-intelligence models for capture-session anomaly detection, bot-vs-human classification, and device-fingerprint-based risk scoring at real-time latency.\n Drive vendor ML strategy by benchmarking external models against a Coinbase-owned evaluation set, designing dynamic routing logic across providers and geographies, and building the in-house evaluation layer that catches regressions before they reach users.\n Lead and mentor senior and mid-level engineers in the pod while partnering with ML Platform and Risk ML teams to align cross-company ML system design.\n \n Required Skills and Experience: \n \n 8+ years deploying production ML systems at scale, with proven technical leadership owning cross-team ML architecture from design through production.\n Domain experience in identity verification, biometrics, or account integrity with deep applied ML in at least two of: computer vision/biometrics, GNNs, sequence models, or NLP/LLMs.\n Expert-level Python with production experience in TensorFlow or PyTorch, including model training, evaluation, and serving infrastructure.\n Track record translating KYC/AML requirements and fraud trends into ML roadmaps and communicating trade-offs to Product, Compliance, Risk, and Security stakeholders.\n Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.\n Pay Transparency Notice: Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)). \n  \n Annual base salary range (excluding equity and bonus):\n $218,025 — $256,500 USD \n \n Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.\n Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws. \n US Applicants: View Employee Rights , Know Your Rights , and E-Verify Notice of Participation. \n Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial . \n Data Privacy \u0026 Arbitration: By submitting your application, you agree to our Candidate Privacy Notice . US applicants: By submitting your application, you agree to Arbitration of Disputes .","salary_min":218025,"salary_max":256500,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["generative-ai","llm","tensorflow","pytorch","computer-vision","nlp","machine-learning"],"apply_url":"https://www.coinbase.com/careers/positions/7891045?gh_jid=7891045","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-10T16:54:42Z","expires_at":"2026-08-14T14:10:59.124156Z","created_at":"2026-06-28T14:08:51.953742Z","updated_at":"2026-07-15T14:10:59.256985Z","company_name":"Coinbase","company_slug":"coinbase","company_logo_url":"https://www.google.com/s2/favicons?domain=www.coinbase.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fd2d788a-a2ca-4ecb-a331-1497714b42e6"},{"id":"f8a2299a-003d-4a9e-9b6d-4fb5ee6b9c23","company_id":"d8e15a46-b80d-4228-8e7b-34f00357f377","title":"Principal Search Consulting Architect","slug":"principal-search-consulting-architect-38429fa6","description":"Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.\n What is the Role \n As a Principal Search Architect , you will serve as the elite technical authority and visionary leader helping our largest enterprise customers unlock the full potential of Elasticsearch . Acting as a strategic, trusted advisor to CTOs and Enterprise Architecture teams, you will design, govern, and scale massive, complex Elasticsearch cluster topologies that transform application search performance, data retrieval infrastructure, and AI-powered semantic search capabilities.\n You will bridge the gap between business strategy and cutting-edge distributed systems engineering, collaborating directly with Elastic’s global Professional Services leadership, Core Engineering, Product Management, and Sales executives. In this high-impact role, you will shape the future of enterprise deployments by driving regional architectural standards, leading critical cluster migrations, and mentoring both Fortune 500 engineering teams and internal Elastic technical staff.\n What You Will Be Doing \n \n Elasticsearch Core Architecture: Translate highly complex business requirements into resilient, next-generation enterprise retrieval architectures built natively on distributed Elasticsearch environments.\n Cluster Governance \u0026 Design: Lead the overarching technical strategy and design authority for high-stakes customer engagements—from initial node blueprinting and capacity planning to custom mappings, shard strategy, Index Lifecycle Management (ILM), and cross-cluster replication (CCR/CCS).\n Advanced Vector Search \u0026 AI Engineering: Design and operationalize cutting-edge semantic search architectures utilizing Elasticsearch’s native vector database capabilities, including kNN, Approximate Nearest Neighbor (ANN), ELSER (Elastic Learned Sparse Encoder), hybrid retrieval, and Retrieval-Augmented Generation (RAG) pipelines.\n Performance Tuning \u0026 Optimization: Profile, benchmark, and tune distributed search and indexing performance for ultra-high-QPS environments with aggressive sub-second SLAs, optimizing Apache Lucene segment merging, caching layers, and heap/garbage collection configurations.\n High-Throughput Indexing: Architect robust distributed ingestion strategies handling petabyte-scale throughput, optimizing cluster state performance, thread pools, and bulk indexing requests for maximum efficiency.\n Cross-Functional Influence: Collaborate cross-functionally with Elastic Product Management and Core Engineering to influence the Elasticsearch codebase roadmap, surface edge-case bugs, and drive feature enhancement requests based on enterprise field realities.\n Community \u0026 IP Development: Capture, formalize, and publish global best practices, reference architectures, and reusable solution patterns across the broader Elasticsearch and open-source engineering communities.\n Culture of Excellence: Drive internal enablement initiatives, mentor senior engineers, and cultivate a culture of continuous technical excellence and deep mastery of Elasticsearch internals.\n \n What You Bring \n \n 8+ years as a Principal Architect, Lead Engineer, or Senior Systems Consultant with recognized, deep technical expertise specifically focused on Elasticsearch at a massive scale.\n Elasticsearch Internals Mastery: Comprehensive understanding of distributed systems theory as it applies to Elasticsearch, including consensus protocols, internal node roles (master, data, ingest, machine learning), Apache Lucene indexing mechanics, and cluster state management.\n AI-Powered Search Expertise: Proven track record of deploying production-grade semantic search solutions using Elasticsearch’s native ML nodes, dense/sparse vector fields, and integrations with modern NLP frameworks and LLM orchestration tools.\n Cloud-Native Infrastructure: Advanced knowledge of orchestrating massive Elasticsearch workloads across cloud platforms (AWS, Azure, GCP) using cloud-native patterns, Docker, and Terraform.\n Polyglot Coding: Strong proficiency in multiple programming languages (e.g., Java, Python, Go) with extensive experience utilizing official Elasticsearch client libraries and building custom plugins.\n Elite Communication: Exceptional presentation and storytelling skills, with verified experience commanding a room of executive stakeholders to align technical Elasticsearch roadmaps with core business strategy.\n Education: Ba","salary_min":191900,"salary_max":303500,"location":"United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["nlp","search","rag","embeddings","llm","distributed-systems"],"apply_url":"https://jobs.elastic.co/jobs?gh_jid=7988387\u0026gh_jid=7988387","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-08T21:02:33Z","expires_at":"2026-08-14T14:10:51.603248Z","created_at":"2026-06-28T14:08:43.714248Z","updated_at":"2026-07-15T14:10:51.752768Z","company_name":"Elastic","company_slug":"elastic","company_logo_url":"https://www.google.com/s2/favicons?domain=www.elastic.co\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f8a2299a-003d-4a9e-9b6d-4fb5ee6b9c23"},{"id":"5e7a8b20-78fc-43da-88e3-7c45f54fb11c","company_id":"f36ec848-cb19-4b95-a680-6733e58086c0","title":"Lead ML/Perception Engineer","slug":"lead-mlperception-engineer-758996b3","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 May Mobility is entering an exciting phase of growth as we expand our first-of-its-kind autonomous shuttle and mobility services across the nation. Launched in 2017 with a strong team of experienced roboticists and software engineers with decades of experience fielding robotic systems in the wild, May Mobility is looking to expand its team of robotics engineers with a background in robotics or autonomous vehicles.\n As Perception Lead, you will own the technical direction of how our vehicles see and interpret the world. This is a hands-on role focused on three priorities: advancing scene detection so the system reliably recognizes its operating context and engages the right behavior; hardening perception against sensor degradation and adverse weather (rain, snow, fog, glare, low light, and sensor soiling or occlusion) so performance degrades gracefully and safely; and driving major architectural updates to evolve our perception stack into a scalable, maintainable, production-grade foundation. You will set the technical bar, mentor engineers, and deliver capabilities that operate safely in the real world.\n Essential Responsibilities \n \n Work independently with cross-functional teams to develop software and system requirements.\n Lead major architectural updates to the perception stack, including system-level design, modularization, and migration strategies that improve scalability, latency, and maintainability across the fleet.\n Design, develop, and own scene detection and activation capabilities, classifying the operating scene/scenario and triggering the appropriate perception behaviors and operational design domain (ODD) logic at runtime.\n Improve perception robustness under degradation and adverse weather, including sensor fault detection, health monitoring, graceful degradation, and fallback strategies for rain, snow, fog, glare, low-light, and sensor soiling/occlusion conditions.\n Design, implement, and test state-of-the-art perception features on time with high quality, industrial-grade production code.\n Integrate large-scale multi-modal models (including but not limited to VLMs and LLMs) into the perception stack to improve semantic scene understanding and reasoning.\n Track and trend technical performance of perception in the field.\n Lead major feature development including feature design, code reviews, issue diagnosis, and resolution.\n Lead extensive testing to validate features and satisfy release schedules.\n Lead development related to data, development, and ML pipelines, specifically focused on multimodal data alignment for training foundation models.\n \n Skills and Abilities \n Success in this role typically requires the following competencies:\n \n Proven ability to architect and evolve large-scale perception or autonomy systems, balancing performance, latency, safety, and long-term maintainability.\n Strong grasp of perception robustness and reliability engineering, including degraded-sensor operation, adverse-weather handling, fault detection, and graceful degradation.\n Experience with scene/scenario understanding and runtime activation logic (e.g., context classification, ODD monitoring, behavior triggering).\n Familiar with ML development cycle, deployment, and optimization.\n Deep understanding of data: data pipeline, data balancing, data mining, and data-driven performance improvement.\n Knowledge of multimodal learning techniques, including contrastive learning and prompt engineering for zero-shot visual recognition.\n Deep understanding of testing frameworks and workflows.\n Excellent attention to detail and rigorous testing methodology.\n Exceptional written and verbal communication skills and team-leading abilities.\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 A minimum of 5+ years of industry experience working on real-world robot systems maintaining high-quality indus","salary_min":235000,"salary_max":275000,"location":"Anywhere","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"lead","tags":["llm","nlp","healthcare","data-pipeline","computer-vision","tensorflow","fine-tuning","generative-ai"],"apply_url":"https://job-boards.greenhouse.io/maymobility/jobs/8582594002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-08T19:14:56Z","expires_at":"2026-08-14T14:20:04.93647Z","created_at":"2026-06-28T14:16:46.571214Z","updated_at":"2026-07-15T14:20:05.035735Z","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/5e7a8b20-78fc-43da-88e3-7c45f54fb11c"},{"id":"2e49713e-2df0-4a5c-9c4e-12f68ec0cd70","company_id":"92df3417-f362-4f1a-9406-e34d8013b283","title":"Senior ML/AI Modeler, Risk Automation Machine Learning","slug":"senior-mlai-modeler-risk-automation-machine-learning-f6cdaff1","description":"Block builds simple, powerful tools that make progress towards an economy that’s truly open to all. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we’re helping build a financial system that is open to everyone. Join us.\n The Role \n The Risk Automation ML team automates Risk and Compliance investigations and decision making at Block through the application of agentic and generative AI technology. We work globally with partners in Product, Engineering and Operations to ensure that we are providing a safe user experience for our customers while minimizing or eliminating bad activity on our platform.\n We are leveraging agentic and generative AI as an integral part of our toolkit to fulfill our mission. Block's machine learning systems monitor billions of payment transactions across traditional payment and blockchain networks and surface suspicious activity (fraudulent, suspicious, illegal activity and brand violations) for trained Operations analyst review and decisioning. We are leveraging generative AI to accelerate historically manually intensive analyst workflows; by adding features in the investigative UX to accelerate agent productivity and enable them to make faster, more informed and accurate decisions (aka Copilots). We also automate workflows end to end completely eliminating the need for manual reviews (aka Autopilots).\n This is a new and significant opportunity to rethink and optimize Risk Operations at Block at scale. This is an IC role, but the senior level has significant leadership responsibilities that include owning, and driving strategic roadmaps \u0026 priorities to completion by collaborating with relevant cross functional stakeholders.\n (Work from anywhere: This role can be performed from any location in the United States and Canada)\n You Will \n \n Experiment and deploy AI copilot and autopilot systems at scale to improve analyst productivity and/or eliminate manual decision loops altogether.\n Own the end to end system including API calls to disparate data sources, advanced prompt tuning, orchestration, metrics and evaluation, productionization and monitoring.\n Leverage diverse data sets that include payment transactions, connected users and asset graphs, unstructured text data and user profile information to build transformer based ML models to improve downstream detection tasks.\n Work cross functionally with product, platform, engineering and operational stakeholders to deploy production grade systems and monitor and tune ongoing performance.\n Use Python ML stack, LLMs, Pytorch, Snowflake, Airflow based tools, data platform and cloud services (both GCP \u0026 AWS) to get the job done.\n Leverage agentic tools (Claude Code/Codex/Openclaw) to supercharge your research, development, devOps and documentation work as part of your day to day.\n \n You Have \n \n 8+ years of Machine Learning modeling experience. Full stack ML experience is strongly preferred.\n A Masters or advanced degree in computer science, data science, operations research, applied math, stats, physics, or a related technical field.\n 3+ yrs experience with AI engineering, Large language models, and a background in traditional NLP techniques is a strong plus for this role.\n End to end experience of building and deploying ML/AI to production systems (batch and real time) that are performant at scale.\n Experience of independently owning, influencing and driving programs with multiple cross functional stakeholders that have significant business impact.\n Have a curious, growth-oriented mindset and the ability to think in first principles to identify creative solutions that demonstrate value.\n \n We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.\n We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible.  Want to learn more about what we're doing to build a workplace that is fair and square? Check out our   I+D page .\n \n \n \n Block t","salary_min":194500,"salary_max":291700,"location":"Seattle, WA","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["llm","payments","nlp","code-generation","agents","cloud","generative-ai","pytorch"],"apply_url":"http://block.xyz/careers/jobs/5198103008?gh_jid=5198103008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-04T05:27:50Z","expires_at":"2026-08-14T14:11:29.102582Z","created_at":"2026-06-28T14:09:10.268278Z","updated_at":"2026-07-15T14:11:29.24176Z","company_name":"Block","company_slug":"block","company_logo_url":"https://www.google.com/s2/favicons?domain=block.xyz\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2e49713e-2df0-4a5c-9c4e-12f68ec0cd70"},{"id":"319d86c6-6524-4f45-bea2-a748b165fa84","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Senior Staff Machine Learning Engineer","slug":"senior-staff-machine-learning-engineer-902cfe64","description":"About the Team\n The Ads \u0026 Promos Delivery team powers the last-mile delivery of ads and promotions, two marketing products offered to merchants, connecting merchant intent with consumer demand across search and discovery experiences. As a Senior Staff Engineer, you will lead the technical direction for AI-first experiences, including ranking and relevance systems that sit at the core of our ads marketplace and shape how ads are selected, ordered, and personalized in real time across all verticals.\n You will design and build next-generation AI-first ranking systems using state-of-the-art techniques such as sequence modeling, deep learning, and large language models (LLMs). Your work will span query understanding, user and merchant representation learning, contextual relevance, and multi-objective optimization, balancing advertiser value, consumer experience, and marketplace health at scale.\n You will set the long-term technical vision, drive cross-team alignment, and translate cutting-edge research into production systems that operate under strict latency, scale, and reliability constraints.\n As DoorDash expands into 40+ global markets and new verticals such as Grocery and Retail, this role offers a rare opportunity to define how modern AI, including sequential models and LLM-powered decisioning, reshapes ads relevance in a closed-loop marketplace.\n About the Role\n \n Apply state-of-the-art machine learning and LLM techniques to problems across personalization, query understanding, user and content understanding.\n Rigorously evaluate ML and LLM models using a combination of offline analysis and online experimentation, designing metrics and experiments that clearly measure quality, impact, and tradeoffs.\n Own the full model lifecycle from research to production, including data analysis, model development, evaluation, offline and online A/B testing, and continuous iteration.\n Partner closely with product managers, data scientists, and designers to ensure AI-driven systems deliver meaningful, user-facing improvements.\n Stay at the forefront of ML and AI innovation by assessing emerging research and translating promising approaches into scalable, production-ready systems.\n \n This is a high-impact role for someone who enjoys combining economic intuition, large-scale ML modeling, and applied engineering to solve complex real-world optimization problems.\n You’re excited about this opportunity because you will…\n \n Own impactful ML systems: Build and improve models that directly have a large impact on top and bottom line financials.\n Collaborate cross-functionally: Partner with engineering, analytics, product, and operations to iterate quickly, moving models from prototype to production\n Shape the future: We're one of the fastest growing Ads platforms in the world and we're looking to take that even further!\n \n We’re excited about you because you have…\n \n 5+ years of experience building, deploying, and scaling ML and AI models for large-scale, user-facing or data-intensive products.\n Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software\n BS, MS, or PhD in Computer Science, Engineering, or a related field, or equivalent practical experience.\n Deep expertise in one or more of the following areas: deep learning, large language models, information retrieval, ranking and relevance, recommendation systems, natural language processing, or content understanding.\n Strong programming skills in Python, Java, or C++, with hands-on experience using ML frameworks such as PyTorch, TensorFlow, or XGBoost.\n Extensive experience across the full ML lifecycle, including data analysis, feature engineering, iterative model development, rigorous offline and online evaluation, and ongoing monitoring and improvement.\n Strong collaborator and communicator who thrives in fast-paced, cross-functional environments.\n Product-minded and impact-driven, with a passion for applying cutting-edge ML and AI techniques to real-world problems.\n \n Bonus Points For\n \n Experience designing and deploying LLM-based systems, including prompt engineering and retrieval-augmented generation (RAG) architectures, Generative RecSys.\n Experience solving large-scale, user-centric and content-centric personalization problems, including user modeling, retrieval, ranking, and relevance.\n Demonstrated contributions to the ML community through open-source projects, publications, or applied research in areas such as ML, NLP, information retrieval, or related fields.\n Compensation \n The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modifi","salary_min":242800,"salary_max":357000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["nlp","search","fine-tuning","cloud","llm","deep-learning","healthcare","pytorch"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/7980080","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-03T23:00:06Z","expires_at":"2026-08-14T14:21:31.863806Z","created_at":"2026-06-28T14:18:07.881887Z","updated_at":"2026-07-15T14:21:31.972803Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/319d86c6-6524-4f45-bea2-a748b165fa84"},{"id":"e881f51c-da1f-4b13-8739-f11fbb53f32a","company_id":"92df3417-f362-4f1a-9406-e34d8013b283","title":"Staff Machine Learning Engineer (Modeling), Support","slug":"staff-machine-learning-engineer-modeling-support-18e1b18d","description":"Block builds simple, powerful tools that make progress towards an economy that’s truly open to all. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we’re helping build a financial system that is open to everyone. Join us.\n The Role \n Block's Support ML Modeling team is a central driver of innovation in customer support experiences across our entire ecosystem—including Cash App, Square, and other business units. We are dedicated to advancing the state of intelligent, automated support through machine learning and generative AI. From customer-facing chatbots to smart internal tools for agents, our team builds high-impact, scalable systems that improve support quality, efficiency, and accessibility.\n We're building the future of support at Block: one powered by AI, voice interfaces, and smart automation. We're looking for candidates with a passion for intelligent systems, practical ML experience, and a desire to build product-driven solutions. Our ideal candidate is a leader in the field, with a proven track record of building ML systems that can accelerate our ability to scale our conversational AI initiatives. \n You Will \n \n Lead the end-to-end delivery of multiple ML initiatives, from planning and design through rollout, documentation, and long-term maintenance\n Partner strategically with risk, product, engineering, design, and operations leaders to define and drive long term ML roadmaps, informed by domain expertise and industry trends\n Guide the team’s direction, identifying new ML/AI opportunities and advising leadership on strategic tradeoffs and opportunities\n Drive R\u0026D efforts exploring next-generation chatbot architectures using LLMs, RAG, fine-tuning, and real-time inference\n Design, deploy, and maintain ML models powering conversational agents including support chatbots across Cash App, Square, and other Block products\n Develop ML-powered tools and real time recommendation systems that enhance support agent effectiveness and customer outcomes\n Act as the technical representative for your team’s systems and programs, clearly communicating work and results to stakeholders, cross-functional partners, and external audiences\n \n You Have \n \n 10+ years of experience in machine learning, applied AI, or product ML roles, with deep technical expertise\n Demonstrated leadership capabilities, with the ability to influence and align cross-functional teams while directly shaping the work of peers through communication, context sharing, and technical guidance\n A track record of delivering organizational wide impact, shaping systems, frameworks, or initiatives that raise the bar across multiple teams or functions\n Proven ability to ship end to end ML features from problem framing through deployment and long-term maintenance\n Demonstrated experience with language models, dialog systems, or generative AI in production\n Strong foundation in NLP, deep learning, or ML infrastructure best practices.\n Excellent communication skills, with the ability to represent the team’s work to leadership and stakeholders\n Enthusiasm for R\u0026D and pushing the boundaries of applied AI to transform conversational systems\n \n Technologies We Use and Teach \n \n Python, PyTorch, TensorFlow, or JAX\n \n We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.\n We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible.  Want to learn more about what we're doing to build a workplace that is fair and square? Check out our   I+D page .\n \n \n \n Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.\n ","salary_min":276800,"salary_max":415200,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["deep-learning","cloud","llm","fine-tuning","pytorch","nlp","generative-ai","tensorflow"],"apply_url":"http://block.xyz/careers/jobs/5198105008?gh_jid=5198105008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-03T21:13:53Z","expires_at":"2026-08-14T14:11:29.652655Z","created_at":"2026-06-28T14:09:10.684398Z","updated_at":"2026-07-15T14:11:29.78472Z","company_name":"Block","company_slug":"block","company_logo_url":"https://www.google.com/s2/favicons?domain=block.xyz\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e881f51c-da1f-4b13-8739-f11fbb53f32a"},{"id":"784c77a7-bf9e-4530-b1e4-01579e0125b3","company_id":"adc4981a-d4ff-4939-952f-362f51e1291d","title":"Sr. Data Scientist","slug":"sr-data-scientist-8c1c1a90","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 About 6sense\n 6sense is revolutionizing how B2B organizations create, manage, and convert pipeline to revenue. Powered by AI, big data, and predictive analytics, our platform helps revenue teams identify buying intent, engage the right accounts, and drive growth.\n The Opportunity\n We're looking for a Senior Data Scientist (IC4) to join our growing AI and Data Science team. This is an exciting opportunity for an experienced ML practitioner who enjoys building production-grade AI systems and transforming cutting-edge research into impactful customer-facing products.\n You will work on advanced machine learning, NLP, LLMs, Agentic AI, and GenAI applications that directly influence product innovation and customer outcomes.\n What You'll Do\n \n Design, build, and deploy scalable machine learning and AI solutions in production environments.\n Develop NLP and transformer-based systems for enterprise-scale applications.\n Build Agentic AI workflows leveraging frameworks such as LangGraph and LangChain.\n Own the end-to-end ML lifecycle, including:\n \n Data exploration\n Feature engineering\n Model development\n Evaluation\n Deployment\n Monitoring\n \n Develop ranking, recommendation, classification, prediction, and optimization models.\n Partner closely with Product, Engineering, and Analytics teams to solve complex business problems.\n Improve performance, scalability, reliability, and observability of production ML systems.\n Contribute to AI platform architecture and technical strategy.\n Mentor engineers and help elevate engineering excellence across the organization.\n \n What We're Looking For\n Required Qualifications\n \n 8+ years of experience building and deploying machine learning solutions in production.\n Strong foundation in Machine Learning, Statistics, and Applied Data Science.\n Experience with:\n \n Supervised \u0026 Unsupervised Learning\n Recommendation Systems\n Ranking Models\n Predictive Modeling\n \n Deep expertise in:\n \n NLP\n Transformers\n Embeddings\n Encoder-Decoder Architectures\n Retrieval-based Systems\n \n Hands-on experience with GenAI ecosystems including:\n \n LangGraph\n LangChain\n Amazon Bedrock\n \n Strong Python programming skills.\n Experience building distributed ML systems and pipelines using AWS and Databricks.\n Strong understanding of feature engineering, model evaluation, and MLOps.\n Ability to independently solve ambiguous problems and drive execution.\n Strong product mindset with focus on customer impact and business outcomes.\n \n Preferred Qualifications\n \n Experience building Agentic AI and Multi-Agent Systems.\n Experience with:\n \n RAG Architectures\n Vector Databases\n Prompt Engineering\n \n Hands-on experience with PyTorch and/or TensorFlow.\n Prior experience in B2B SaaS or customer-facing AI products.\n \n Base Salary Range: $162,923.67 - $238,954.71 . 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 take advantage of health coverage, paid parental leave, generous paid time-off and holidays, quarterly self-care days off, and stock options. We’ll make sure you have the equipment and support you need to work and connect with your teams, at home or in one of our offices.  \n We have a growth mindset culture that is represented in all that we do, from onboarding through to numerous learning and development initiatives including access to our LinkedIn Learning platform. Employee well-being is also top of mind for us. We host quarterly wellness education sessions to encourage self care and personal growth. 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