{"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":"8e714354-f0cc-4558-b706-5f155771b9bb","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Technical Lead Manager, Machine Learning Runtime \u0026 Serving","slug":"technical-lead-manager-machine-learning-runtime-serving-3bc85bbd","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n Waymo is seeking a senior Technical Lead Manager (TLM) Machine Learning Engineer to guide the technical vision of our core ML infrastructure. In this role, you will actively grow and manage a high-performing team of 6 engineers to deliver Waymo’s next-generation ML ecosystem. This critical work encompasses both the in-vehicle inference engine and the cloud-based serving infrastructure for our foundational models. You will architect scalable, high-performance ML runtime systems that operate across two extreme domains: the highly constrained edge compute environment of autonomous vehicles and our large-scale, offboard data centers.\n You will: \n \n Guide the technical vision of our core ML infrastructure while actively growing and managing a high-performing team of 6 engineers to deliver Waymo’s next-generation ML ecosystem, encompassing both the in-vehicle inference engine and the cloud-based serving infrastructure for our foundational models.\n Architect scalable, high-performance ML runtime systems that operate flawlessly across two extreme domains: the highly constrained edge compute environment of autonomous vehicles and our large-scale, offboard data centers.\n Navigate complex engineering trade-offs, driving feature development that seamlessly balances the strict, real-time latency and memory limits of onboard execution with the high-throughput, highly concurrent demands of fleet-scale cloud serving.\n Spearhead the strategic transition of core ML workloads to a JAX-native runtime architecture, which includes actively extending and modifying underlying ML compilers and runtimes (e.g., OpenXLA/PjRT, TensorRT).\n Partner across organizational boundaries with world-class ML researchers in Perception and Planning to deeply analyze system-level workloads and unlock massive performance gains through hardware-aware compute optimizations.\n Drive systemic performance excellence by designing advanced profiling and benchmarking infrastructure to identify, triage, and eliminate bottlenecks across the entire end-to-end ML software stack.\n \n You have: \n \n B.S. or M.S. in CS, EE, Deep Learning or a related field.\n People management experience, with a proven track record of recruiting, mentoring, and guiding high-performing teams of senior engineers.\n 8+ years of professional software engineering experience architecting, building, and scaling complex ML systems and infrastructure.\n Strong production programming expertise.\n Proven track record of optimizing ML software to maximize the performance of hardware accelerators (e.g., GPUs, TPUs, or custom silicon).\n Hands-on experience developing distributed backend systems that are low-latency, highly concurrent, and fault-tolerant at scale.\n \n We prefer:  \n \n PhD in CS, EE, Deep Learning or a related field.\n Deep expertise in modifying and extending ML software stacks, including compilers, runtimes, or inference engines (e.g., OpenXLA/PjRT, TensorRT, ONNX Runtime, TVM).\n Strong background in building and scaling LLM serving systems, leveraging advanced distributed inference and performance optimization techniques.\n Deep expertise in edge computing and automotive ML deployment, navigating strict power, thermal, and real-time latency constraints to optimize and deploy mission-critical models on resource-constrained embedded hardware.\n \n \n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $251,000 — $310,000 USD","salary_min":251000,"salary_max":310000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["deep-learning","autonomous-vehicles","llm","machine-learning"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8062303","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-15T01:09:13Z","expires_at":"2026-08-14T14:06:32.954628Z","created_at":"2026-07-15T14:06:33.079101Z","updated_at":"2026-07-15T14:06:33.079101Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8e714354-f0cc-4558-b706-5f155771b9bb"},{"id":"d3e4d203-9a98-43d2-b9d4-af63039179a3","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Machine Learning Engineer, Sensor Pipelines","slug":"machine-learning-engineer-sensor-pipelines-d82bbef2","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n The Perception team at Waymo builds technology that powers the Waymo Driver. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We conduct research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling software engineers like you to develop multi-modal models and techniques at scale.\n The Sensor Pipelines team applies sensor fusion and ML approaches to address critical challenges in Perception; like detections of Collisions, Antagonistic Behaviors like Vandalism, Sensing Occlusions, etc. Our work involves cutting-edge research (Gen AI) to solve real-world problems and requires close collaboration with onboard teams across Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to develop sophisticated models and techniques at scale.\n This role follows a hybrid work schedule and reports to a Technical Lead Manager.\n You will: \n \n Apply sensor fusion, machine learning techniques to build multi-modal sensor fusion architectures and spatial-temporal representation learners to solve real-world challenges\n Develop and deploy machine learning models, including using Generative Artificial Intelligence (Gen AI) system, and non-ML systems to solve those challenging problems\n Develop data mining, labeling, training and eval pipelines to support the onboard development\n Collaborate and work in partnership with product, infra and research teams across Waymo\n \n You have: \n \n Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience\n 3+ years experience in Machine Learning and/or Computer Vision\n Experience with C++ and Python\n Experience with ML frameworks like PyTorch or JAX\n \n We prefer: \n \n MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline\n Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI\n Github repositories or Tech Blogs of LLMs/ VLMs\n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $175,000 — $215,000 USD","salary_min":175000,"salary_max":215000,"location":"Mountain View, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["pytorch","autonomous-vehicles","computer-vision","llm","deep-learning","generative-ai","robotics","machine-learning"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8051390","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T20:03:11Z","expires_at":"2026-08-14T14:06:24.797122Z","created_at":"2026-07-15T14:06:24.923116Z","updated_at":"2026-07-15T14:06:24.923116Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d3e4d203-9a98-43d2-b9d4-af63039179a3"},{"id":"dbf3ed2d-61a8-46d4-8f99-13cd04d28f0e","company_id":"4c109027-78ec-41cd-b57a-dc58e47d0bd0","title":"Senior Machine Learning Scientist I, Model-Driven Optimization","slug":"senior-machine-learning-scientist-i-model-driven-optimization-eb80e6bd","description":"The Role:  \n Generate:Biomedicines is seeking a creative, rigorous, and execution-oriented machine learning scientist to join our Model-Driven Design team. This role will focus on building the ML methods, data strategies, and closed-loop systems that determine what we design, build, test, and learn from next.\n The Model-Driven Design team works at the interface of machine learning, protein design, engineering, and experimental science. We develop and apply models and quantitative frameworks that help Generate discover and optimize therapeutic proteins. In this role, you will help advance the technical foundation of our lab-in-the-loop protein optimization platform, with a focus on sequential decision-making, experimental design, property modeling, and scalable design systems.\n We are looking for someone who can serve as a technical leader and hands-on individual contributor, driving complex, high-impact work from problem framing through implementation, deployment, and experimental impact. The ideal candidate combines depth in probabilistic machine learning, Bayesian optimization, active learning, or related approaches with the practical judgment and engineering discipline to turn technical ideas into reliable systems that drive impact. You will partner closely with protein designers, wet-lab scientists, ML scientists, and engineers to build durable capabilities that accelerate therapeutic discovery.\n This role is part of a highly collaborative team environment that balances in-person collaboration with hybrid flexibility based out of our Somerville, MA office. \n Here's how you will contribute: \n \n Develop new machine learning methods and systems for lab-in-the-loop protein optimization, including property models and multi-objective optimization strategies for therapeutic protein design.\n Shape data-generation and data-use strategies that make experimental campaigns maximally informative for model improvement, therapeutic optimization, and future design cycles.\n Build and apply LLM-enabled and agentic workflows that help scientists explore design hypotheses, connect models to data and experiments, and accelerate iterative learning.\n Design, implement, test, and maintain production-quality ML models, software components, and data workflows, with attention to reliability, reproducibility, observability, and computational efficiency.\n Partner with ML engineering and software teams to integrate these components into robust, scalable platform capabilities, with clear ownership across team boundaries.\n Collaborate closely with protein designers and wet-lab scientists to ensure models and optimization systems are grounded in experimental reality and deliver measurable impact.\n Identify important technical gaps, develop proposals, define milestones, align stakeholders, and help set technical direction across cross-functional programs.\n Communicate clearly across disciplines and help raise technical standards across ML, engineering, protein design, and experimental teams.\n \n The Ideal Candidate will have: \n \n PhD in machine learning, computational biology, computer science, applied mathematics, engineering, or a related quantitative field.\n Strong practical experience with probabilistic machine learning, Bayesian optimization, active learning, experimental design, or related approaches for sequential decision-making under uncertainty.\n Experience developing machine learning methods or systems for biological, biomedical, or experimental scientific data, with an ability to reason about noisy assays, sparse labels, experimental bias, and data-generation strategy.\n Demonstrated ability to translate ML ideas into systems, tools, or workflows that affect real scientific, experimental, or product decisions.\n Strong Python skills and experience with modern ML frameworks such as PyTorch, JAX, or similar tools.\n Strong systems thinking and ability to design technical interfaces, reason about system tradeoffs, and partner with engineering teams to build scalable, maintainable ML infrastructure.\n Excellent communication skills and ability to bridge ML, engineering, protein design, and experimental stakeholders.\n Pragmatic, collaborative working style, with the ability to bring structure to open-ended problems and balance scientific rigor with execution in fast-moving, cross-functional environments.\n \n Nice to have \n \n Experience in protein design, protein engineering, antibody engineering, biologics discovery, or drug development.\n Experience partnering with experimental teams on design-build-test-learn cycles, high-throughput screening, directed evolution, pooled libraries, or model-guided experimental campaigns.\n Experience with multi-objective optimization, uncertainty calibration, model-guided library design, or experimental campaign planning.\n Experience developing and applying deep learning models, including transformer-based architectures\n Experience building or applying LLM agents, scientific copilots, or agentic syste","salary_min":192000,"salary_max":265000,"location":"Somerville, MA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","llm","healthcare","code-generation","deep-learning","pytorch","machine-learning"],"apply_url":"https://generatebiomedicines.com/open-positions?gh_jid=4696856006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T19:16:51Z","expires_at":"2026-08-14T14:15:56.335011Z","created_at":"2026-07-15T14:15:56.439634Z","updated_at":"2026-07-15T14:15:56.439634Z","company_name":"Generate Biomedicines","company_slug":"generate-biomedicines","company_logo_url":"https://www.google.com/s2/favicons?domain=generatebiomedicines.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/dbf3ed2d-61a8-46d4-8f99-13cd04d28f0e"},{"id":"724ab66f-d426-4c39-b31e-1b432c22d253","company_id":"83c597c2-a4b2-4517-99df-1ac8c90756d5","title":"Senior Simulation Vehicle Modeling Engineer","slug":"senior-simulation-vehicle-modeling-engineer-9867b4f8","description":"About the Company  \n At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners.  Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer. \n Meet The Team:   \n At Torc, our simulation teams are building the foundation for AV 3.0 driver-out development and certification. This team serves as the critical technical interface between simulation/modeling and autonomy consumers. By ensuring model fidelity, coverage, and usability, the team plays a vital role in evaluating and advancing autonomous driving software. We support massive-scale, parallel execution for scaled verification and validation (V\u0026V) and high-throughput reinforcement learning (RL) training. Ultimately, we provide the framework and tooling that serves Autonomy, Safety, and Release with shared artifacts, common metrics, and deterministic reproducibility.    \n What You'll Do:   \n \n Develop and own vehicle dynamics models, including high-fidelity truck models that accurately represent longitudinal, lateral, and transient behavior for use in simulation and autonomy validation.  \n Design, develop, and maintain high-fidelity simulation platforms used to validate autonomous driving software in closed-loop evaluation pipelines at scale.   \n Partner with autonomy engineering teams to capture and implement vehicle model requirements that support planning, controls, and system-level V\u0026V activities.   \n Own model capability communication, known limitations, and release notes to enable effective autonomy validation.   \n Ensure vehicle model updates do not regress autonomy V\u0026V system performance by using automated regression frameworks.   \n Execute full software development lifecycle activities primarily in C++ within a Linux development environment and ROS/ROS2 tooling, applying Lean-Agile methodologies.   \n Perform root cause analysis on issues identified during simulation runs and hardware-in-the-loop testing.   \n Participate in designing test plans for data acquisition and telemetry that support field data collection for vehicle model refinement.   \n Support system-level test plans and verification strategies.   \n Communicate progress, design decisions, and blockers clearly at daily stand-ups and design reviews.   \n Build and maintain collaborative relationships with OEM partners and simulation tool vendors to evaluate, integrate, and co-develop simulation capabilities.   \n \n What You'll Need to Succeed:   \n \n Bachelor's Degree in Computer Science, Robotics, Mechanical Engineering, Electrical Engineering, or a related technical field plus 6+ years of relevant experience; or Master's Degree in the above fields plus 3+ years of relevant experience; or  PhD in the above fields plus 1+ years of relevant experience.   \n Proficiency in C++ (primary), Python for tooling and ML integrations, ROS/ROS2, CMake, and Linux.   \n Physics-based modeling of ground vehicles, including longitudinal/lateral dynamics, tire models, and powertrain.   \n Working knowledge of AV autonomy stack architecture—planning, controls, and system integration—to collaborate effectively with autonomy engineering teams and ensure vehicle models meet V\u0026V requirements.   \n Ability to translate vehicle model capabilities and limitations to autonomy engineering teams, and to capture their requirements to inform model fidelity improvement initiatives.   \n Experience with unit, integration, and regression testing, as well as automated validation pipelines and simulation-based performance benchmarking.   \n Expected to drive consensus across simulation, autonomy, controls, and product engineering \u0026 safety teams.   \n Ability to own and maintain key technical systems across multiple repositories and contribute to cross-org architectural decisions.   \n Must operate as an advanced-level professional with wide latitude for independent judgment and minimal supervision.   \n Willingness to mentor and guide engineers within the group and contribute to technical direction within the simulation and autonomy domains.   \n \n Bonus Points!   \n \n Experience with high-fidelity truck \u0026 trailer or heavy-vehicle models.  \n Experience building or extending closed-loop autonomous vehicle simulation environments.   \n Familiarity with scenario-based validation and sim-to-real correlation activities.   \n Familiarity with how learned models (neural networks) consume simulation and vehicle model outputs in autonomy V\u0026V workflows.   \n \n Perks of Being a Full-time Torc’r   \n Torc cares about our team members and we strive","salary_min":160800,"salary_max":193000,"location":"Ann Arbor, MI","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["payments","robotics","reinforcement-learning","autonomous-vehicles","deep-learning"],"apply_url":"https://job-boards.greenhouse.io/torcrobotics/jobs/8624508002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T18:27:34Z","expires_at":"2026-08-14T14:07:36.10117Z","created_at":"2026-07-15T14:07:36.22853Z","updated_at":"2026-07-15T14:07:36.22853Z","company_name":"Torc Robotics","company_slug":"torc-robotics","company_logo_url":"https://www.google.com/s2/favicons?domain=torc.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/724ab66f-d426-4c39-b31e-1b432c22d253"},{"id":"b5fee987-f2ea-4b80-a04f-395e616158d8","company_id":"c93e0284-9c76-4a85-9905-494865ab9278","title":"AI Systems Performance Engineer - New Graduate","slug":"ai-systems-performance-engineer-new-graduate-e4bfa2f7","description":"The era of pervasive AI has arrived. In this era, organizations will use generative AI to unlock hidden value in their data, accelerate processes, reduce costs, drive efficiency and innovation to fundamentally transform their businesses and operations at scale. \n SambaNova Suite™ is the first full-stack, generative AI platform, from chip to model, optimized for enterprise and government organizations. Powered by the intelligent SN40L chip, the SambaNova Suite is a fully integrated platform, delivered on-premises or in the cloud, combined with state-of-the-art open-source models that can be easily and securely fine-tuned using customer data for greater accuracy. Once adapted with customer data, customers retain model ownership in perpetuity, so they can turn generative AI into one of their most valuable assets. \n About The Role \n We are seeking a talented and highly motivated AI Systems Performance Engineer to bring up and optimize state-of-the-art foundation models on SambaNova's reconfigurable dataflow platform.\n You'll work hands-on with advanced AI models — such as DeepSeek, GLM, Kimi, GPT OSS, Llama, Qwen, and other frontier architectures — and learn how modern AI systems achieve high throughput, low latency, and efficient large-scale inference.\n In this role, you'll work at the intersection of machine learning and computer systems, collaborating with engineers across model, compiler, runtime, and hardware teams. This is an ideal opportunity for a new graduate who is passionate about understanding how AI models execute on real hardware and wants to help build the next generation of high-performance AI systems.\n Responsibilities \n \n Bring up cutting-edge foundation models, including LLMs and multimodal models, on the SambaNova platform through the SambaNova software stack.\n Analyze and profile model execution to identify performance bottlenecks across model, compiler, runtime, and hardware layers.\n Optimize AI workloads for throughput, latency, memory efficiency, and scalability.\n Collaborate with machine learning, compiler, runtime, and hardware engineers to develop high-performance AI applications.\n Explore and integrate new techniques in model architecture, quantization, scheduling, caching, and memory optimization.\n Develop tools, benchmarks, and performance analysis methodologies for large-scale AI inference.\n Investigate new model architectures and translate research advances into efficient implementations on production AI systems.\n Contribute ideas for dataflow, scheduling, and system optimizations for both single-node and distributed inference.\n \n Basic Qualifications \n \n Bachelor's or Master's degree in computer science, electrical engineering, computer engineering, or a related technical field (e.g., applied mathematics, physics, or statistics), completed or expected before the start date.\n Strong programming skills in Python, C++, or a similar programming language.\n Solid foundations in algorithms, data structures, computer architecture, operating systems, or parallel computing.\n Familiarity with deep learning and at least one major ML framework, such as PyTorch, TensorFlow, or JAX.\n Strong analytical and problem-solving skills, with an interest in understanding and optimizing system performance.\n Ability and enthusiasm to learn across machine learning, software systems, and hardware.\n \n Preferred Qualifications \n \n Coursework, research, internship, or project experience in machine learning systems, computer architecture, compilers, distributed systems, or high-performance computing.\n Hands-on experience with LLMs, multimodal models, or transformer architectures.\n Familiarity with model inference, KV cache, batching, quantization, or distributed execution.\n Experience with GPU or accelerator programming using CUDA, Triton, OpenCL, or similar technologies.\n Familiarity with frameworks such as vLLM, DeepSpeed, Megatron, or TensorRT.\n Understanding of memory hierarchy, caching, parallelism, or scheduling.\n Experience profiling and optimizing the performance of software or ML workloads.\n Research publications, open-source contributions, programming competitions, or technically challenging personal projects are a plus.\n \n We value strong technical fundamentals, curiosity, and the ability to learn quickly. Prior production experience with large-scale AI systems is not required.\n Base Salary Range:\n Base Pay Range\n $135,000 — $165,000 USD \n Submission Guidelines Please note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified.  \n EEO Policy SambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex ","salary_min":135000,"salary_max":165000,"location":"San Jose, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["llm","gpu","distributed-systems","deep-learning","tensorflow","generative-ai","pytorch"],"apply_url":"https://sambanova.ai/sambanova-available-positions/?gh_jid=6115124004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T22:28:28Z","expires_at":"2026-08-14T14:06:10.228422Z","created_at":"2026-07-15T14:06:10.360035Z","updated_at":"2026-07-15T14:06:10.360035Z","company_name":"SambaNova Systems","company_slug":"sambanova","company_logo_url":"https://www.google.com/s2/favicons?domain=sambanova.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b5fee987-f2ea-4b80-a04f-395e616158d8"},{"id":"71ee758f-16cd-4c69-8fc0-3f12619c37ad","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Staff Machine Learning Engineer, Simulation ","slug":"staff-machine-learning-engineer-simulation-353a3819","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack.\n In this hybrid role, you will report to an Engineering Manager  \n You will: \n \n Report into the TLM for the Learned Metrics Team\n Develop ML models that assess our autonomous vehicle's behavior.\n Develop ML infrastructure to support performant models.\n Collaborate across teams to bring state-of-the-art to production.\n \n You have: \n \n BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area, or equivalent work experience\n 5+ years of experience building productionized ML models\n Code and design skills: comfort building production systems (Python / C++)\n Background in applied Deep Learning\n A track record in improving model quality\n \n We prefer: \n \n 8+ years of experience building productionized ML models\n Experience in reinforcement learning, transfer learning, or learning.\n Experience with large scale data and models\n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $251,000 — $310,000 USD","salary_min":251000,"salary_max":310000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","robotics","deep-learning","autonomous-vehicles","machine-learning"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8056720","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T22:11:43Z","expires_at":"2026-08-14T14:06:31.087662Z","created_at":"2026-07-15T14:06:31.242063Z","updated_at":"2026-07-15T14:06:31.242063Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/71ee758f-16cd-4c69-8fc0-3f12619c37ad"},{"id":"e57cf48d-3756-4016-8e50-400a76bbaa5d","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Staff Machine Learning Engineer, Computer Vision","slug":"staff-machine-learning-engineer-computer-vision-147d8a7f","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n Within Pinterest, the Pinterest Labs organization focuses on applied ML research and development. Labs works across a broad variety of AI/ML initiatives—including core computer vision, multimodal representation learning, heterogeneous graph neural networks, generative modeling, and recommender systems. This is the group that develops the foundation ML models that fully leverage the tens of billions of Pins and the associated knowledge graph to improve the core product.\n We are currently hiring for the Visual Modeling team in Labs, which develops Pinterest's in-house visual encoder. In this role, you'll work with Pinterest's rich visual-text dataset to train large-scale models from scratch that are continuously shipped to production to power visualization features. You'll build multimodal representations that power applications such as recommender systems, Semantic IDs, and a range of downstream ML models. The visual encoder also produces visual tokens that power our in-house VLM and composed image retrieval models. The core visual pod is a small group (~10 engineers) inside Labs, which allows for deep collaboration. For example, engineers working on multimodal representation also contribute to our internal text-to-image generation Canvas project—collaborating on autoencoder design or on reward function development for RL training.\n  \n What you’ll do: \n \n Prototype state-of-the-art visual encoders that power Pinterest's recommender systems and internal visual language models.\n Experiment with billion-scale datasets and gain hands-on experience with large-scale GPU computing.\n Build flexible visual reasoning tools such as composed image retrieval, promptable detection/segmentation, and instruction-tuned embedding and generative models.\n Read research papers, participate in group discussions, and help brainstorm the company's overall visual generative strategy.\n Help collect relevant visual instruction training data that can be shared across multimodal representation, composed image retrieval, text-to-image generation and visual language modeling.\n Publish and share your work through conferences, paper submissions, and blog posts.\n Mentor junior researchers and research interns within the Pinterest Labs organization.\n  \n \n What we’re looking for: \n \n Research engineers and scientists with experience building and training computer vision models.\n Experience with multimodal representations and visual language modeling is strongly preferred.\n A track record of research contributions (e.g., publications, open-source work) and/or shipping ML models to production.\n Hands-on experience with large-scale model training and modern deep learning frameworks (e.g., PyTorch).\n Strong collaboration skills and a demonstrated ability to work effectively in a small, fast-moving team.\n M.S. or PhD in Machine Learning or related academic areas, or equivalent work experience.\n Publications at top ML conferences\n Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring\n \n  \n Relocation Statement: \n \n This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.\n \n  \n In-Office Requirement Statement: \n \n We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.\n This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.\n \n  \n #LI-REMOTE #LI-AK7\n At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The posit","salary_min":189308,"salary_max":389753,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"lead","tags":["deep-learning","search","generative-ai","code-generation","computer-vision","pytorch","machine-learning"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8015537","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T17:51:37Z","expires_at":"2026-08-14T14:10:33.819803Z","created_at":"2026-07-15T14:10:33.975738Z","updated_at":"2026-07-15T14:10:33.975738Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e57cf48d-3756-4016-8e50-400a76bbaa5d"},{"id":"26f6fd92-b550-42db-86b5-5699c2c31afc","company_id":"75dcf7c0-5121-45f1-8d1b-6bfbfe15072f","title":"Helix AI Engineer, Localization and Mapping","slug":"helix-ai-engineer-localization-and-mapping-9de55455","description":"Figure is on a mission to develop and deploy general purpose humanoid robots for corporate tasks targeting labor shortages and jobs that are undesirable or unsafe. We are looking for passionate and motivated superstars to grow our world-class team. We are based in Sunnyvale, CA and require 5 days/week in-office collaboration. It’s time to build.\n Figure’s vision is to deploy autonomous humanoids at a global scale. Our AI team is looking for Localization and Mapping Engineers to empower Figure humanoid robots to perform highly dynamic operations in demanding real-world environments.\n Responsibilities: \n \n Architect and implement real-time localization, ego-motion tracking, and state estimation systems by fusing multi-modal sensor data (cameras, IMUs, encoders, magnetic sensors).\n Build and maintain scalable, offline pose-tracking pipelines to process large-scale training data from diverse sources.\n Develop and optimize multi-sensor calibration systems for humanoid robotics and data collection platforms.\n Partner with cross-functional teams to build comprehensive, data-driven evaluation and testing frameworks.\n Design, engineer, and deploy high-quality, reliable software solutions for real-world robotics applications.\n \n Required Qualifications: \n \n Deep technical expertise in solving complex estimation and nonlinear optimization problems.\n Strong command of 3D geometry, visual-inertial SLAM, and computer vision techniques, including feature matching/tracking, and Structure from Motion (SfM).\n Experience writing performant C++ software.\n Hands-on experience with sensor calibration (e.g., multi-camera and IMU intrinsics/extrinsics).\n Ability to thrive in a fast-paced, ambiguous environment that requires rapid exploration and iteration.\n Passion for advancing humanoid robotics technology.\n \n Bonus Qualifications: \n \n Experience implementing visual-inertial SLAM systems on legged robotic platforms.\n Background in estimation problems related to human motion capture or AR/VR applications.\n Experience applying state-of-the-art Deep Learning approaches to SLAM, 3D reconstruction, or human pose estimation.\n \n The US base salary range for this full-time position is between $200,000 - $400,000\n The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.","salary_min":200000,"salary_max":400000,"location":"San Jose, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["computer-graphics","computer-vision","fine-tuning","deep-learning","robotics"],"apply_url":"https://job-boards.greenhouse.io/figureai/jobs/4696533006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T16:02:44Z","expires_at":"2026-08-14T14:07:52.541231Z","created_at":"2026-07-15T14:07:52.665427Z","updated_at":"2026-07-15T14:07:52.665427Z","company_name":"Figure AI","company_slug":"figure-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=figure.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/26f6fd92-b550-42db-86b5-5699c2c31afc"},{"id":"cb44c455-97e8-4e00-ab4f-3fab00fa325f","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Staff Machine Learning Engineer","slug":"staff-machine-learning-engineer-586d7131","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 Job Duties: Design, develop, and train advanced machine learning models, including deep neural networks, transformer-based architectures, and reinforcement learning systems, to power large-scale online advertising ranking and optimization platforms. Lead the development and optimization of complex feature representations, including high-dimensional embeddings, contextual and temporal signals, and cross-session user behavior modeling. Drive end-to-end model lifecycle execution, including system architecture design, large-scale experimentation, model deployment, performance monitoring, and iterative infrastructure improvements in production environments. Collaborate closely with product, data, and infrastructure engineering teams to translate business objectives into scalable, statistically rigorous modeling solutions. Conduct advanced experiment design and causal analysis to evaluate model impact and inform strategic decisions. Provide technical leadership and mentorship to machine learning engineers and contribute to organization-wide modeling standards, best practices, and long-term technical strategy. Shape the long-term modeling vision across multiple advertising domains, including conversion optimization, application advertising, shopping, and brand advertising. Full-time telecommuting is an option. \n Requirements: Master’s degree in Computer Science, Engineering (any field) or related quantitative discipline and (3) three years of experience in the job offered or related occupation. \n Special Skill Requirements: 1) Python, Java, and Scala; 2) C++, Go, or Rust; 3) major machine learning frameworks and libraries; 4) applied statistics, hypothesis testing and experiment design for online machine learning systems; 5) large-scale data processing and analytics frameworks; 6) deployment and operation of production systems in containerized and distributed environments; 7) Designing and training advanced models, including deep neural networks, transformer-based architectures, and reinforcement learning models; 8) marketplace dynamics, such as real-time bidding (RTB) or pacing control systems; 9) developing and optimizing online advertising systems, including ad ranking, targeting, and market place; 10) providing technical leadership, mentorship, or guidance to other machine learning engineers. Any suitable combination of education, training and/or experience is acceptable. Full-time telecommuting is an option. \n Benefits: \n \n Comprehensive Healthcare Benefits and Income Replacement Programs\n 401k with Employer Match\n Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support\n Family Planning Support\n Gender-Affirming Care\n Mental Health \u0026 Coaching Benefits\n Flexible Vacation \u0026 Paid Volunteer Time Off\n Generous Paid Parental Leave \n \n Submit a resume with references using the apply button on this posting or by email at:  applicationsreview@reddit.com at Req.# 1016.83.2.\n  \n Pay Transparency: \n This job posting may span more than one career level.\n In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit  https://www.redditinc.com/careers/ .\n To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. \n The base pay range for this position is: $230,000.00 - $322,000.00 USD\n  \n #LI-DNI\n In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.\n During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We ","salary_min":230000,"salary_max":322000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["healthcare","mlops","reinforcement-learning","deep-learning","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/8054426","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T13:51:13Z","expires_at":"2026-08-14T14:10:39.416828Z","created_at":"2026-07-15T14:10:39.537452Z","updated_at":"2026-07-15T14:10:39.537452Z","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/cb44c455-97e8-4e00-ab4f-3fab00fa325f"},{"id":"8e37b314-f237-44dc-a850-dd58524233c1","company_id":"19a78c6a-11dc-4d21-8273-0d2d2bad39b1","title":"Staff Data Scientist","slug":"staff-data-scientist-9bba8726","description":"Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.\n As a Staff Data Scientist, you’ll lead the design and development of scalable ML systems for use cases such as menu recommendation, demand forecasting, offer targeting, and guest personalization. You will serve as a technical thought partner across teams, set best practices, and influence the roadmap for ML-driven products that support key business outcomes. Your work will directly shape strategic decisions and enhance customer experience at scale.  \n This role is for a current vacancy.\n A day in the life (Responsibilities) \n \n Own the full machine learning lifecycle—from problem framing and data exploration to modeling, deployment, and monitoring—for mission-critical initiatives.\n Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights.\n Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy.\n Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization.\n Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise.\n Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward.\n Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.\n \n  \n What you'll need to thrive (Requirements) \n \n 5+ years of experience in data science with a proven track record of delivering production ML systems that drive measurable impact.\n Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.\n Experience working with real-world product data at scale and translating ambiguous problems into well-scoped ML solutions.\n Experience with distributed data processing and training, real-time inference, and ML Ops frameworks\n Prior experience mentoring other data scientists or acting as a tech lead.\n Experience leading experimentation (e.g., A/B testing), causal inference, and real-time decision systems.\n Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).\n Strong grasp of software engineering principles including modular design, version control, testing, and CI/CD.\n Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.\n Excellent communication skills and the ability to influence both technical and non-technical stakeholders.\n Strong business acumen with the ability to align technical solutions with company goals.\n \n Bonus ingredients* : \n \n An advanced degree in Computer Science, Statistics, or a related STEM field is preferred.\n Familiarity with MLOps tooling for monitoring, drift detection, retraining, and explainability.\n Experience fine-tuning LLMs and applying reinforcement learning from human feedback (RLHF) to improve model performance and alignment.\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 #LI-Remote\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 $127,000 — $203,000 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 focus","salary_min":127000,"salary_max":203000,"location":"Canada","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["tensorflow","reinforcement-learning","deep-learning","mlops","llm","pytorch","fine-tuning","data-science"],"apply_url":"https://careers.toasttab.com/jobs?gh_jid=8052293","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T20:25:38Z","expires_at":"2026-08-14T14:11:50.57728Z","created_at":"2026-07-09T14:09:45.188959Z","updated_at":"2026-07-15T14:11:50.703686Z","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/8e37b314-f237-44dc-a850-dd58524233c1"},{"id":"f04f6e13-ccf2-458b-8576-e7fa94481050","company_id":"19a78c6a-11dc-4d21-8273-0d2d2bad39b1","title":"Staff Data Scientist","slug":"staff-data-scientist-317fda4d","description":"Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.\n As a Staff Data Scientist, you’ll lead the design and development of scalable ML systems for use cases such as menu recommendation, demand forecasting, offer targeting, and guest personalization. You will serve as a technical thought partner across teams, set best practices, and influence the roadmap for ML-driven products that support key business outcomes. Your work will directly shape strategic decisions and enhance customer experience at scale.\n A day in the life (Responsibilities) \n \n Own the full machine learning lifecycle—from problem framing and data exploration to modeling, deployment, and monitoring—for mission-critical initiatives.\n Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights.\n Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy.\n Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization.\n Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise.\n Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward.\n Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.\n \n  \n What you'll need to thrive (Requirements) \n \n 7+ years of experience in data science with a proven track record of delivering production ML systems that drive measurable impact.\n Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.\n Experience working with real-world product data at scale and translating ambiguous problems into well-scoped ML solutions.\n Experience with distributed data processing and training, real-time inference, and ML Ops frameworks\n Prior experience mentoring other data scientists or acting as a tech lead.\n Experience leading experimentation (e.g., A/B testing), causal inference, and real-time decision systems.\n Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).\n Strong grasp of software engineering principles including modular design, version control, testing, and CI/CD.\n Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.\n Excellent communication skills and the ability to influence both technical and non-technical stakeholders.\n Strong business acumen with the ability to align technical solutions with company goals.\n Experience building services on top of LLMs in a large scale production environment.\n \n Bonus ingredients* : \n \n An advanced degree in Computer Science, Statistics, or a related STEM field is preferred.\n Familiarity with MLOps tooling for monitoring, drift detection, retraining, and explainability.\n Experience fine-tuning LLMs and applying reinforcement learning from human feedback (RLHF) to improve model performance and alignment.\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 #LI-Remote\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 $170,000 — $272,000 USD \n Zone B\n $148,000 — $237,000 USD \n Zone C\n $133,000 — $213,000 USD \n How Toast Uses AI in its Hiring Process \n Throughout ","salary_min":133000,"salary_max":213000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["pytorch","tensorflow","reinforcement-learning","fine-tuning","deep-learning","mlops","llm","data-science"],"apply_url":"https://careers.toasttab.com/jobs?gh_jid=8029049","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T20:23:10Z","expires_at":"2026-08-14T14:11:50.505714Z","created_at":"2026-07-09T14:09:45.268862Z","updated_at":"2026-07-15T14:11:50.63104Z","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/f04f6e13-ccf2-458b-8576-e7fa94481050"},{"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":"d6456870-ff5c-4c3f-89d2-a6e8784670b8","company_id":"57a9b50d-a69a-4f6f-9acb-910495c3c359","title":"MTS, Research Engineer","slug":"mts-research-engineer-69babe33","description":"About Us: \n At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n About the Role \n We are looking for a Research Engineer to join our team, operating at the critical intersection of model research and training infrastructure.\n In this role, your time will be split between tackling open-ended research problems—such as designing novel architectures and improving algorithmic efficiency — and building the distributed training systems required to make those research breakthroughs a reality. You won't just be handed a paper to implement; you will be expected to reproduce state-of-the-art results from the literature, identify their limitations, and build the infrastructure needed to push beyond them.\n The most significant advances in deep learning require massive scale. We need engineers who are as comfortable reasoning about gradient descent and loss landscapes as they are about distributed systems, GPU cluster utilization, and data pipelines.\n  \n What You'll Do \n \n Conduct Open-Ended Research: Explore new model architectures, training objectives, and optimization techniques. Formulate hypotheses, design experiments, and iterate quickly based on empirical results.\n Reproduce and Extend State-of-the-Art: Implement and reproduce results from recent machine learning papers. Identify bottlenecks, propose improvements, and scale these methods to larger datasets and models.\n Build and Scale Training Infrastructure: Design, implement, and maintain high-performance, distributed machine learning systems. Optimize training loops, data loaders, and communication overhead across large GPU clusters.\n Bridge Science and Engineering: Translate abstract mathematical concepts and research ideas into robust, bug-free, and efficient code.\n Collaborate Cross-Functionally: Work closely with Research Scientists to unblock their experiments by providing tooling, optimizing code, and co-designing experiments that are hardware-aware.\n \n We Expect You To Have: \n \n Strong programming skills (Python, C++, or Rust) and a commitment to writing clean, maintainable code.\n Deep practical knowledge of machine learning frameworks (PyTorch, JAX, or TensorFlow).\n Experience working with large distributed systems and parallel computing (e.g., CUDA, NCCL, MPI).\n A strong foundation in linear algebra, calculus, probability, and statistics.\n A proven track record of implementing complex deep learning algorithms from scratch.\n \n Nice to Have: \n \n A Master’s or PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related field (or equivalent industry experience).\n Experience with low-level GPU programming (CUDA/Triton) or hardware co-design.\n Familiarity with the challenges of training Large Language Models (LLMs)\n Familiarity with the challenges of inference, and OSS inference engines such as SGLang and vLLM\n Total compensation for this role also includes meaningful equity in a fast-growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.\n Base Pay Range (Plus Equity)\n $250,000 — $400,000 USD \n Why Fireworks AI? \n \n Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n Ownership \u0026 Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n \n Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.","salary_min":250000,"salary_max":400000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["gpu","search","deep-learning","tensorflow","distributed-systems","generative-ai","pytorch","data-pipeline"],"apply_url":"https://job-boards.greenhouse.io/fireworksai/jobs/4308305009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T01:55:35Z","expires_at":"2026-08-14T14:02:25.80437Z","created_at":"2026-07-09T14:02:13.613892Z","updated_at":"2026-07-15T14:02:25.938275Z","company_name":"Fireworks AI","company_slug":"fireworks-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=fireworks.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d6456870-ff5c-4c3f-89d2-a6e8784670b8"},{"id":"6d36576b-fa47-4e5e-86a5-1462935721f7","company_id":"ec4a8bb4-3840-4054-8ccd-77e81db037af","title":"Lead Software Engineer - Generative AI ","slug":"lead-software-engineer-generative-ai-46968d3b","description":"C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI \n We are looking for a highly skilled and experienced lead software engineer experienced in the field of machine learning and artificial intelligence, and passionate about Generative AI technology and building next-generation software platforms.\n As a member of C3 AI’s Generative AI team, you will be tasked with developing the infrastructure and tools to improve the state-of-the-art and enable the use of this game changing technology in our enterprise applications. You’ll collaborate with product managers, data scientists and other engineers and will be responsible for the entire software engineering lifecycle. A successful candidate will thrive in a fast-paced, innovative, and highly collaborative environment, and demonstrate an ability to execute precisely and quickly. The ideal candidate will have in-depth experience with putting large scale machine learning models in production and a solid understanding of Large Language Models (LLMs).\n Responsibilities: \n \n Work across teams to architect robust software engineering solutions and frameworks with cross product impact.\n Implement and enhance engineering best practices company wide.\n Build systems and tools to enable and simplify the use of Generative AI technologies in our applications using the C3 AI Platform.\n Enable scalable end-to-end machine learning pipelines in a distributed system with heterogeneous hardware (GPUs, TPUs, etc.).\n Work with data scientists to research and implement latest approaches to efficiently train/fine-tune Generative Models.\n Work with product owners to define and lead the long-term development the C3 Generative AI Suite.\n Lead cross-team technical design discussions on application architecture, UI components, UX, back-end and third-party integration, and testing.\n Manage individual project deliverables and mentor junior team members on industry coding standards and design techniques.\n \n Qualifications: \n \n Bachelor's degree in Computer Science, Computer Engineering, or related fields, MS preferred.\n 8+ years of professional software development experience in Python; experience with Java and JavaScript preferred.\n Proven track record of design and development of full stack web solutions for complex problems.\n Strong hands-on experience and understanding of data structures, algorithms, profiling/optimization, DRY code, and Object-Oriented and Functional Programming.\n In-depth understanding of machine learning including deep learning algorithms.\n Proven track record of applying machine learning algorithms in a production system.\n Demonstrated end-to-end ownership of projects.\u2028\n Excellent verbal and written communication skills to collaborate multi-functionally and improve scalability.\n Demonstrated interest for Generative AI technology (e.g., projects with technologies like LangChain, Semantic Kernel, ChatGPT Plugins, etc.).\n \n Preferred Qualifications: \n \n Advanced degree in computer science, math, or similar quantitative field.\n Knowledge of Agile development methodology.\n Experience in leading engineering teams and projects.\n \n  \n C3 AI provides excellent benefits, a competitive compensation package and generous equity plan. \n California Base Pay Range\n $175,000 — $219,000 USD \n C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.","salary_min":175000,"salary_max":219000,"location":"Redwood City, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","deep-learning","agents","generative-ai","distributed-systems"],"apply_url":"https://c3.ai/job-description/8623467002?gh_jid=8623467002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-07T23:05:40Z","expires_at":"2026-08-14T14:11:56.044458Z","created_at":"2026-07-09T14:09:50.667518Z","updated_at":"2026-07-15T14:11:56.186902Z","company_name":"C3 AI","company_slug":"c3-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=c3.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6d36576b-fa47-4e5e-86a5-1462935721f7"},{"id":"7f79fea2-20fb-4786-8450-9206f440b721","company_id":"ec4a8bb4-3840-4054-8ccd-77e81db037af","title":"Senior Software Engineer - Generative AI ","slug":"senior-software-engineer-generative-ai-3be69168","description":"C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI \n We are looking for a seasoned software engineer experienced in the field of machine learning and artificial intelligence, and passionate about Generative AI technology and building next-generation software platforms.\n As a member of C3 AI’s Generative AI team, you will be tasked with developing the infrastructure and tools to improve the state-of-the-art and enable the use of this game changing technology in our enterprise applications. You’ll collaborate with product managers, data scientists and other engineers and be responsible for the entire software engineering lifecycle. A successful candidate will thrive in a fast-paced, innovative, and highly collaborative environment, and demonstrate an ability to execute precisely and quickly. The ideal candidate will have in-depth experience with putting large scale machine learning models in production and a solid understanding of Large Language Models (LLMs).\n Responsibilities: \n \n Build systems and tools to enable and simplify the use of Generative AI technologies in our applications using the C3 AI Platform.\n Enable scalable end-to-end machine learning pipelines in a distributed system with heterogeneous hardware (GPUs, TPUs, etc.).\n Work with data scientists to research and implement latest approaches to efficiently train/fine-tune Generative Models.\n Work with product owners to define and lead the long-term development the C3 Generative AI Suite.\n Mentor junior members of the team.\n \n Qualifications: \n \n Bachelor's degree in Computer Science, Computer Engineering, or related fields, MS preferred.\n Excellent programming skills in Python; experience with Java and JavaScript preferred.\n Thorough knowledge of data structures, algorithms, profiling/optimization, DRY code, and Object-Oriented and Functional Programming.\n In-depth understanding of machine learning including deep learning algorithms.\n Track record of applying machine learning algorithms in a production system.\n Demonstrated end-to-end ownership of projects.\u2028\n Stellar listening and explanation skills.\n Demonstrated interest for Generative AI technology (e.g., projects with technologies like LangChain, Semantic Kernel, ChatGPT Plugins, etc.).\n A minimum of 3 years of work experience in a fast-paced software company.\n \n Preferred Qualifications: \n \n Advanced degree in computer science, math, or similar quantitative field.\n Knowledge of Agile development methodology.\n 5+ years of work experience in a fast-paced software company.\n C3 AI provides excellent benefits, a competitive compensation package and generous equity plan. \n California Base Pay Range\n $150,000 — $198,000 USD \n C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.","salary_min":150000,"salary_max":198000,"location":"Redwood City, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","deep-learning","agents","generative-ai","distributed-systems"],"apply_url":"https://c3.ai/job-description/8623459002?gh_jid=8623459002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-07T23:03:21Z","expires_at":"2026-08-14T14:11:58.063167Z","created_at":"2026-07-09T14:09:52.592128Z","updated_at":"2026-07-15T14:11:58.191467Z","company_name":"C3 AI","company_slug":"c3-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=c3.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7f79fea2-20fb-4786-8450-9206f440b721"},{"id":"4ee45bf1-b8e9-4cdd-a230-51d0059bd127","company_id":"ccb23d77-c69e-462b-a941-02ce99527e78","title":"Senior Software Engineer, Perception","slug":"senior-software-engineer-perception-cb375ed5","description":"Who we are \n Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.\n The Aurora Driver  will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone.\n  \n At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit  aurora.tech  or follow us on  LinkedIn .\n  \n Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We’re searching for a Senior Software Engineer, Perception to join our autonomous driving team. In this role, you will collaborate closely with cross-functional engineering teams to design and deploy state-of-the-art machine learning models directly onto our real-time vehicle platform. This is an exciting opportunity to solve complex, high-impact autonomy challenges and directly shape the future of the Aurora Driver.\n In this role, you will \n \n Develop and Optimize Core Perception Solutions: Research and develop state-of-the-art deep learning and machine learning models to improve perception under challenging scenarios, such as long-range multi-sensor detection and degraded sensor conditions.\n Tackle End-to-End Autonomy Challenges: Address object detection, tracking of traffic actors, action recognition, and semantic understanding of diverse traffic scenes.\n Deploy Production-Ready Software: Guide software development from initial prototype to production deployment on a real-time AV platform, leveraging large-scale data sets for training and analysis.\n Collaborate and Iterate: Partner with team members to diagnose, analyze, and resolve failure modes encountered during on-road and simulated testing to produce robust, well-tested systems.\n Scale ML Engineering Pipelines: Build and scale robust ML pipelines to facilitate quick experimentation as well as large-scale training and testing.\n \n   \n Required Qualifications \n \n BS, MS, or PhD in Computer Science, Robotics, Engineering, or a related field with a strong foundation in one or more focus areas of ML, including deep learning, computer vision, recursive state estimation, structured prediction, and optimization.\n 6+ years of research-based or professional experience with C++ and Python .\n Comprehensive grasp of linear algebra, discrete/continuous optimization, supervised/unsupervised methods, and generative/discriminative models.\n Strong publication record at top-tier robotics/computer vision conferences/journals, or significant industry experience in relevant fields (robotics, computer vision, self-driving technology)\n \n   \n Desirable Qualifications \n \n Experience utilizing deep learning frameworks such as PyTorch or TensorFlow .\n Advanced production-level knowledge of C++ is highly preferred.\n Prior experience applying computer vision and machine learning directly to complex robotics problems.\n Experience deploying computer vision/ML models at scale across large physical fleets.\n Proven ability to work effectively in environments requiring close cross-team collaboration.\n Experience working with 3D data, including 3D object detection, tracking, semantic segmentation, or processing point clouds from LiDAR, Radar, and multi-camera system\n \n  \n The base Salary range for this position is $162,000 - $260,000.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits. \n  #LI-td-1 #Mid-Senior \n Working at Aurora At Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks.\n We believe in-person work increases collaboration, empathy and our ability to lead effectively. As a result, we operate in a hybrid work environment where Aurorans are in office at least 3 days per week.\n Our Careers page provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom .\n Our commitment to safety \n At the core of everything we do is our commitment to safety. Building best-in-class self-driving technology will take time, and we believe that each employee at Aurora has a role in contributing to safety, every step of the way. Aurora expects commitment to our safety policies from every employee, and seeks candidates who take an active responsibili","salary_min":162000,"salary_max":260000,"location":"Mountain View, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["computer-vision","autonomous-vehicles","pytorch","deep-learning","robotics","tensorflow"],"apply_url":"https://aurora.tech/jobs/8604304002?gh_jid=8604304002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-07T23:03:08Z","expires_at":"2026-08-14T14:06:40.624903Z","created_at":"2026-07-09T14:04:51.543619Z","updated_at":"2026-07-15T14:06:40.757913Z","company_name":"Aurora Innovation","company_slug":"aurora-innovation","company_logo_url":"https://www.google.com/s2/favicons?domain=aurora.tech\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4ee45bf1-b8e9-4cdd-a230-51d0059bd127"},{"id":"c79e0087-291f-4c4a-a2b7-23c8d0389df7","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Senior Data Scientist, Systems Performance","slug":"senior-data-scientist-systems-performance-690960a2","description":"Mission Summary: \n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas.\n Rigorous behavioral and system performance evaluation is critical to scaling our service and achieving Motional's long-term goals. We are seeking a Senior Data Scientist to lead initiatives that improve evaluation and testing methodologies, measure the quality and trustworthiness of our evaluation portfolio, and partner with engineering teams to monitor and strengthen the health of the evaluation ecosystem. You will help ensure Motional's performance evaluation is efficient, scientifically rigorous, and aligned with our growth priorities.\n In this role, you will lead development of evaluation methodologies and metrics that assess the quality and business relevance of solutions spanning on-road and off-board data. You will influence the evaluation signals software engineers rely on to validate that changes to the autonomy stack deliver intended improvements, conduct deep-dive analyses to understand bottlenecks in current methodologies, and prototype improvements in metrics, sampling strategy, and statistical inference. You will develop deep expertise in how evaluation signals inform launch and release decisions, weigh trade-offs across the evaluation portfolio, and provide actionable insights for designing launch criteria.\n If you are a rigorous, collaborative data scientist with a passion for improving how autonomous systems are measured and validated at scale, we encourage you to apply. \n What You’ll Be Doing: \n \n Lead the development of evaluation frameworks for the autonomous system, connecting technical problems to rigorous, data-driven approaches for measuring and validating performance. \n Collaborate closely with Functional Safety and Systems Engineering teams to ensure evaluation metrics map effectively to automotive safety standards (e.g., SOTIF, ISO 21448) and launch readiness decisions.\n Ensure evaluation metrics are reliable enough to inform safety cases and launch readiness decisions.\n Monitor the reliability of evaluation metrics and incoming performance data over time, including detecting drift, inconsistencies, and degradation in metric definitions, to ensure the evaluation ecosystem remains accurate and trustworthy.\n Drive our approach to performance analysis using data-backed statistical methods for simulation and on-road data.\n Develop new statistical analysis methods to analyze AV performance data and lead by example in applying them to real problems.\n Partner with triage operators and simulation engineers to turn raw disengagements and identified edge cases into procedural or generative scenarios, feeding them back into the simulation catalog to strengthen test coverage.\n Use fleet and evaluation data to identify edge cases in an automated manner and coverage gaps, and partner with engineering to feed novel scenarios back into the simulation catalog and strengthen test coverage.\n Build confidence in the evaluation framework through data-driven insights and clear communication of findings to technical leaders and stakeholders.\n Establish correlation between on-road and simulation data to improve how we interpret and act on evaluation results.\n Make sense of large datasets to drive insights, solve ambiguous performance questions, and communicate results effectively across teams and upward to leadership.\n Establish a self-service model for developers to understand the impact of their changes.\n Develop new metrics, interpret trends, and investigate anomalies in simulation and on-road data. \n Collaborate with developers to drive action based on these results.\n Serve as an advisor and influence collaborators across multiple teams, promote data-aware decision making, and establish best practices around the use of data.\n Mentor and collaborate with fellow engineers and foster a positive, collaborative work environment.\n Introduce the use of ML methods for performance evaluation where they add rigor and scale. \n \n What You Bring: \n \n 5+ years of industry experience solving complex problems with large datasets, with a track record of framing ambiguous questions into rigorous, data-driven analyses.\n Bachelor's or higher degree in Computer Science, Computer Engineering, Data Science, Robotics, Physics, Mathematics, or a related quantitative field. Master's or PhD preferred.\n Strong problem-solving skills: ability to break down complex performance and evaluation challenges, think logically, and remove bias from how problems are defined and assessed.\n Strong Python and SQL skills, with demonstrated expe","salary_min":149000,"salary_max":198000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["mlops","deep-learning","autonomous-vehicles","robotics","data-pipeline","data-science"],"apply_url":"https://motional.com/open-positions/?gh_jid=7797913003#/7797913003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-07T17:01:19Z","expires_at":"2026-08-14T14:08:00.692798Z","created_at":"2026-07-09T14:06:16.041532Z","updated_at":"2026-07-15T14:08:00.822991Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c79e0087-291f-4c4a-a2b7-23c8d0389df7"},{"id":"9f1b93ad-406e-4e80-bb2a-b711316f683b","company_id":"332b7698-676b-4a3e-8b02-81b1195c5af6","title":"Sr. Engineering Manager, AI Runtime","slug":"sr-engineering-manager-ai-runtime-7a4b44d6","description":"At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.\n Databricks' AI Runtime (AIR) product provides enterprises with an API for training and fine-tuning deep learning and LLM models with on-demand GPUs. Whether it's a transformer model for drug discovery or a fine-tuned foundation model, customers use this team's training infrastructure to build state-of-the-art frontier models.\n As a Senior Engineering Manager, you will lead the team owning both the product experience and the foundational infrastructure of AIR. You'll shape customer-facing capabilities while designing for scalability, extensibility, and performance of GPU training and adjacent areas, collaborating closely across the platform, product, infrastructure, and research organizations.\n The impact you will have:\n \n Lead, mentor, and grow a high-performing engineering team responsible for the Custom Training product and its foundational infrastructure, including distributed training orchestration, cluster lifecycle, fault tolerance, and training efficiency.\n Define and own the product and technical roadmap for AIR, balancing customer experience, functionality, and foundational investments.\n Collaborate closely with product, research, platform, infrastructure teams, and customers to drive end-to-end delivery, from ideation and prioritization to launch and operation.\n Drive architectural decisions and product design for managed GPU training at scale.\n Advocate for customer needs through direct engagement, ensuring engineering decisions translate to clear product impact.\n Build observability and reliability practices for long-running, multi-node training jobs, including checkpoint strategies, failure recovery, and operational runbooks.\n Partner with recruiting to attract, hire, and develop top-tier engineering talent.\n \n What we look for:\n \n 8+ years of software engineering experience, with 3+ years in engineering management.\n Track record building and operating managed GPU training infrastructure at scale (100s/1000s GPUs).\n Deep familiarity with distributed training frameworks (PyTorch, DeepSpeed, Composer, Megatron-LM) and parallelism strategies (FSDP, tensor/pipeline parallelism).\n Experience with training resilience patterns: checkpointing, elastic training, and automated failure recovery for long-running jobs.\n Understanding of GPU performance fundamentals including NCCL, interconnect topologies, and memory optimization.\n Experience building platform products with clear SLAs where you've owned the customer experience, not just the backend.\n Strong cross-functional leadership across platform, product, and research teams, with the ability to lead through ambiguity and deliver complex projects.\n Excellent collaboration and communication skills across engineering, product, and research organizations.\n BS/MS in Computer Science, Electrical Engineering, or related technical field.\n \n  \n  \n Pay Range Transparency \n Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . \n  \n Local Pay Range\n $228,600 — $297,120 USD \n About Databricks \n Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on  Twitter ,  LinkedIn   and   Facebook . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . \n Our Commitment to Diversity and Inclusion \n At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiri","salary_min":228600,"salary_max":297120,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","generative-ai","llm","deep-learning","data-pipeline","fine-tuning","pytorch"],"apply_url":"https://databricks.com/company/careers/open-positions/job?gh_jid=8621706002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-06T20:42:50Z","expires_at":"2026-08-14T14:02:32.790896Z","created_at":"2026-07-09T14:02:19.696359Z","updated_at":"2026-07-15T14:02:32.926377Z","company_name":"Databricks","company_slug":"databricks","company_logo_url":"https://www.google.com/s2/favicons?domain=databricks.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9f1b93ad-406e-4e80-bb2a-b711316f683b"},{"id":"14676fa7-bb83-4273-8813-75933b96fb9a","company_id":"099a8aa7-a1bc-4a90-aa8d-f59f677b925a","title":"Senior AI Research Engineer","slug":"senior-ai-research-engineer-154db2b5","description":"Agility’s commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.\n About The Role \n The AI innovation team at Agility works on building and deploying next-generation robot foundation models and end-to-end policies on humanoid robots. Your goal will be to develop and test cutting-edge methods for imitation learning and reinforcement learning on humanoid robots, in order to establish the techniques necessary for humanoid robots to perform different real-world tasks. You will work on a team, running experiments on humanoid robots, and will research and implement methods which can be transferred into production. \n About the Work \n \n Design, train, and deploy robust policies for locomotion, manipulation, and dynamic interactions with the environment. \n Develop core reinforcement learning infrastructure, including scalable training pipelines and evaluation frameworks. \n Design and implement new simulation environments and tasks to support training and deployment of control policies. \n Develop, design, and test imitation learning methods \n Collaborate with Robotics Software and AI engineering teams to develop policies which can be transferred to production \n \n About You \n \n 3+ years of experience developing and deploying learning-from-demonstration \n Strong programming skills in Python, with proficiency in deep learning frameworks such as PyTorch. \n Experience with modern learning-from-demonstration tools like DiffusionPolicy \n Experience with robot data collection, training, and testing on hardware to perform manipulation tasks. \n Ability to work collaboratively in a fast-paced environment to deliver safe, high-quality software \n MS in Robotics, Computer Science, or a related field. \n \n Bonus Points \n \n PhD in Robotics, Computer Science, or a related field. \n Publications in top ML or robotics conferences (e.g. NeurIPS, ICML, CoRL, RSS, ICRA). \n Familiarity with robot simulation environments (e.g. Mujoco, Isaac Sim) and sim-to-real transfer techniques. \n Experience with modern reinforcement learning techniques for locomotion, manipulation, and whole-body control \n Experience with writing performant, high quality software in C++ \n \n This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices.\n The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future. \n  \n Anticipated Salary Range\n $195,000 — $304,000 USD \n In addition to base pay, our competitive total rewards package consists of the following for full-time employees: \n \n 401(k) Plan:   Includes a 6% company match.\n Equity:   Company stock options.\n Insurance Coverage:   100% company-paid medical, dental, vision, and short/long-term disability insurance for employees.\n Benefit Start Date:   Eligible for benefits on your first day of employment.\n Well-Being Support:   Employee Assistance Program (EAP).\n Time Off: \n \n Exempt Employees:   Flexible, unlimited PTO and 12 company holidays, including a winter shutdown.\n Non-Exempt Employees:   10 vacation days, paid sick leave, and 12 company holidays, including a winter shutdown, annually.\n \n On-Site Perks:   Catered lunches four times a week and a variety of healthy snacks and refreshments at our Salem and Pittsburgh locations.\n Parental Leave:   Generous paid parental leave programs.\n Work Environment:   A culture that supports flexible work arrangements.\n Growth Opportunities:   Professional development and tuition reimbursement programs.\n Relocation Assistance:   Provided for eligible roles.\n Annual Discretionary Bonus: Provided for eligible roles.\n \n All of our roles are U.S.-based. Applicants must have current authorization to work in the United States. \n Agility Robotics is committed to a work environment in which all individuals are treated with respect and dignity. Each individual has the right to work in a professional atmosphere that promotes equal employment opportunities and prohibits unlawful discriminatory practices, including harassment. Therefore, it is the policy of Agility Robotics to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law. Agility Robotics prohibits any such discrimination or harassment. \n  \n Agility Robotics does not accept unsolicited referrals from third-party recruiti","salary_min":195000,"salary_max":304000,"location":"Pittsburgh, PA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pytorch","generative-ai","deep-learning","reinforcement-learning","robotics","search","research"],"apply_url":"https://www.agilityrobotics.com/about/job-post?gh_jid=6032175004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-02T21:15:01Z","expires_at":"2026-08-14T14:14:42.950203Z","created_at":"2026-07-03T14:12:21.104796Z","updated_at":"2026-07-15T14:14:43.050249Z","company_name":"Agility Robotics","company_slug":"agility-robotics","company_logo_url":"https://www.google.com/s2/favicons?domain=agilityrobotics.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/14676fa7-bb83-4273-8813-75933b96fb9a"},{"id":"16cc35ff-c277-4fa2-97ba-55a0048a0b21","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Senior Data Scientist, Systems Performance","slug":"senior-data-scientist-systems-performance-cf30584b","description":"Mission Summary: \n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas.\n Rigorous behavioral and system performance evaluation is critical to scaling our service and achieving Motional's long-term goals. We are seeking a Senior Data Scientist to lead initiatives that improve evaluation and testing methodologies, measure the quality and trustworthiness of our evaluation portfolio, and partner with engineering teams to monitor and strengthen the health of the evaluation ecosystem. You will help ensure Motional's performance evaluation is efficient, scientifically rigorous, and aligned with our growth priorities.\n In this role, you will lead development of evaluation methodologies and metrics that assess the quality and business relevance of solutions spanning on-road and off-board data. You will influence the evaluation signals software engineers rely on to validate that changes to the autonomy stack deliver intended improvements, conduct deep-dive analyses to understand bottlenecks in current methodologies, and prototype improvements in metrics, sampling strategy, and statistical inference. You will develop deep expertise in how evaluation signals inform launch and release decisions, weigh trade-offs across the evaluation portfolio, and provide actionable insights for designing launch criteria.\n If you are a rigorous, collaborative data scientist with a passion for improving how autonomous systems are measured and validated at scale, we encourage you to apply. \n What You’ll Be Doing: \n \n Lead the development of evaluation frameworks for the autonomous system, connecting technical problems to rigorous, data-driven approaches for measuring and validating performance. \n Collaborate closely with Functional Safety and Systems Engineering teams to ensure evaluation metrics map effectively to automotive safety standards (e.g., SOTIF, ISO 21448) and launch readiness decisions.\n Ensure evaluation metrics are reliable enough to inform safety cases and launch readiness decisions.\n Monitor the reliability of evaluation metrics and incoming performance data over time, including detecting drift, inconsistencies, and degradation in metric definitions, to ensure the evaluation ecosystem remains accurate and trustworthy.\n Drive our approach to performance analysis using data-backed statistical methods for simulation and on-road data.\n Develop new statistical analysis methods to analyze AV performance data and lead by example in applying them to real problems.\n Partner with triage operators and simulation engineers to turn raw disengagements and identified edge cases into procedural or generative scenarios, feeding them back into the simulation catalog to strengthen test coverage.\n Use fleet and evaluation data to identify edge cases in an automated manner and coverage gaps, and partner with engineering to feed novel scenarios back into the simulation catalog and strengthen test coverage.\n Build confidence in the evaluation framework through data-driven insights and clear communication of findings to technical leaders and stakeholders.\n Establish correlation between on-road and simulation data to improve how we interpret and act on evaluation results.\n Make sense of large datasets to drive insights, solve ambiguous performance questions, and communicate results effectively across teams and upward to leadership.\n Establish a self-service model for developers to understand the impact of their changes.\n Develop new metrics, interpret trends, and investigate anomalies in simulation and on-road data. \n Collaborate with developers to drive action based on these results.\n Serve as an advisor and influence collaborators across multiple teams, promote data-aware decision making, and establish best practices around the use of data.\n Mentor and collaborate with fellow engineers and foster a positive, collaborative work environment.\n Introduce the use of ML methods for performance evaluation where they add rigor and scale. \n \n What You Bring: \n \n 5+ years of industry experience solving complex problems with large datasets, with a track record of framing ambiguous questions into rigorous, data-driven analyses.\n Bachelor's or higher degree in Computer Science, Computer Engineering, Data Science, Robotics, Physics, Mathematics, or a related quantitative field. Master's or PhD preferred.\n Strong problem-solving skills: ability to break down complex performance and evaluation challenges, think logically, and remove bias from how problems are defined and assessed.\n Strong Python and SQL skills, with demonstrated expe","salary_min":149000,"salary_max":198500,"location":"Las Vegas, Nevada, United States","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["mlops","deep-learning","autonomous-vehicles","robotics","data-pipeline","data-science"],"apply_url":"https://motional.com/open-positions/?gh_jid=7792500003#/7792500003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-02T14:03:55Z","expires_at":"2026-08-14T14:08:00.928122Z","created_at":"2026-07-03T14:05:53.429797Z","updated_at":"2026-07-15T14:08:01.051833Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/16cc35ff-c277-4fa2-97ba-55a0048a0b21"}],"market_demand_pack":{"amount_cents":2900,"api_checkout_url":"https://aidevboard.com/api/v1/checkout?product_id=aidevboard_ai_skills_demand_pack","checkout_url":"https://aidevboard.com/market-demand-pack?qc=api-jobs-market-demand-pack\u0026utm_campaign=skills_demand_pack\u0026utm_medium=jobs_api\u0026utm_source=api","currency":"USD","description":"Full ranked public AI/ML demand CSV, source job URLs, and decision brief with market and offer angles.","fulfillment":"automatic_email_after_paid_checkout","human_checkout_url":"https://aidevboard.com/market-demand-pack?qc=api-jobs-market-demand-pack\u0026utm_campaign=skills_demand_pack\u0026utm_medium=jobs_api\u0026utm_source=api","name":"AI Market Demand Pack","next_step":"Open checkout_url for Stripe Checkout, or call api_checkout_url to get the non-charging checkout handoff payload.","price_usd":29,"product_id":"aidevboard_ai_skills_demand_pack","quote_url":"https://aidevboard.com/api/v1/quote?product_id=aidevboard_ai_skills_demand_pack"},"page":1,"per_page":20,"total":766,"total_pages":39}