{"schemaVersion":"jobsearcher.job.v1","id":"979fb88ecff107cd83c19ae4","url":"https://jobsearcher.com/jobs/979fb88ecff107cd83c19ae4","canonicalUrl":"https://jobsearcher.com/jobs/979fb88ecff107cd83c19ae4","title":"Machine Learning Engineer, Data Mining","description":"Our teams are made up of engineers, researchers, innovators, dreamers, and doers. Together, we can change the world.\r\nAll Motional open positions and applications will be posted here on the official website.\r\nInfrastructurePrincipal Machine Learning Engineer, Data MiningBoston, Las Vegas, Pittsburgh, Remote U.S. Only\r\nAt Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag , our ML-powered multimodal data mining framework, is the engine that powers this discovery. As a Principal Machine Learning Engineer, you will serve as a foundational technical leader shaping the long-term, multi-year vision for our foundation model post-training ecosystem. While training foundation models from scratch is on our horizon, your immediate mandate is to architect the systems that adapt, align, and optimize massive multimodal models for our autonomy stack.\r\nArmed with a strong sense of product, you will ensure our technical investments directly translate into downstream value, accelerating edge-case discovery, reducing engineering costs, and improving the final autonomous driving product. You will tackle highly complex, ambiguous problems, creating clarity and defining objectives that pay future dividends for the entire company. By championing deep cross-team collaboration, you will seamlessly connect ML capabilities with our Autonomy and Infrastructure organizations, breaking down silos to ensure smooth execution. Operating at the highest levels of technical maturity, you will solve the hardest technical challenges that few others can, setting the standard for state-of-the-art model distillation, advanced alignment techniques, automated agentic reasoning workflows, and the ultra-efficient deployment of billion-parameter models.\r\nWhat You'll Do:\r\nSet the Technical Direction for Data Mining:Define the multi-year ML roadmap for our multimodal data-mining platform (Omnitag). Turn complex, ambiguous problems into clear objectives, balancing long-term foundational investments (e.g., agentic pipelines) with short-term tactical goals to drive maximum impact.\r\nBuild the Data Flywheel:Own the full lifecycle of our ML data pipelines to close the active-learning loop. You will align massive multimodal teacher models and distill them into efficient student models for exabyte-scale search, accelerating model error diagnosis and reducing compute costs for automated curation.\r\nArchitect Massive-Scale Systems & Tackle the Hardest Challenges:Design the architecture for applying billion-parameter models to real-world AV logs. As the lead implementer for our toughest technical bottlenecks, you will push the boundaries of parameter-efficient fine-tuning, optimize inference latency for large-scale retrieval, and build RL-driven reasoning systems—all while proactively managing system reliability and cloud footprint.\r\nChampion Cross-Functional Initiatives:Act as the technical bridge between Data Mining, Autonomy, and Infrastructure. Armed with a strong product sense, you will deeply understand the edge cases the autonomy stack needs to solve next and coordinate phased rollouts to seamlessly integrate new discovery capabilities into the core AV development loop.\r\nLead and Grow a High-Performing Pod:Serve as a hands-on player-coach, directly guiding up to 3 engineers. Delegate ownership, coach your team to deliver state-of-the-art implementations, and advocate for tooling and practices that elevate developer productivity and reinforce Motional's culture of engineering excellence.\r\nWhat We're Looking For (Must-Haves):\r\nBS in Computer Science, Machine Learning, or a related field, or equivalent professional experience.\r\n12+ years of hands-on machine learning engineering experience, with a proven track record of owning the end-to-end development cycle of enterprise-scale ML systems, from experiment design through infrastructure, testing, rollout, monitoring, and iteration.\r\nExceptional technical maturity, with a track record of building and shipping impact that is innovative, broad in reach (affecting many teams or orgs), and pays future dividends for the company.\r\nProven ability to solve technical problems that few others can, the person others seek out for complex ML infrastructure, deep learning architectures, and production optimization.\r\nDeep experience training large-scale models from the ground up, including distributed training across multi-node GPU clusters, data pipeline and curation strategy, scaling and evaluation methodology, and the practical debugging of large training runs.\r\nDemonstrated ownership of a technical roadmap for a team or problem area, including balancing competing objectives (impact, quality, engineering time, compute cost) and making deliberate tradeoffs between long-term foundational investment and short-term tactical goals.\r\nAbility to create clarity from ambiguous, complex problems, decomposing them concisely, defining objectives, and establishing measures of progress for yourself and your team.\r\nDeep, generalist ML expertise spanning massive-scale model training, hardware-optimized deployment, and production ML orchestration in cloud environments (AWS, GCP, or Azure).\r\nExperience leading cross-team initiatives, including coordinating phased rollouts and migrations across dependent teams, and mentoring engineers to raise the bar around you.\r\nStrong oral and written communication skills. You can clearly explain complex technical problems using data and analysis, and communicate proposals in a way that earns buy-in and creates alignment.\r\nBonus Points (Nice-to-Haves):\r\nMS/PhD in Computer Science, Machine Learning, or a related field.\r\nExperience as a Tech Lead Manager (TLM) or in direct people management, coaching and growing small teams of 2–3 engineers.\r\nBackground in autonomous driving, robotics, or complex real-time decision-making systems.\r\nExperience with massive-scale ML data mining, multimodal foundation models, and embodied AI.\r\nHands-on experience pretraining or post-training a foundation model, data curation at scale, pretraining or continued-pretraining recipes, SFT/RLHF or other alignment methods, and evaluation harness design.\r\nExperience with model compression and adaptation at scale, knowledge distillation (teacher/student), parameter-efficient fine-tuning, or quantization for high-throughput inference.\r\nExperience with large-scale retrieval or search systems, or RL for reasoning and decision-making.\r\nDeep knowledge of enterprise model serving (TF Serving, Triton, TorchServe) and modern MLOps platforms.\r\nExperience building agentic pipelines or LLM-driven reasoning and tool-use workflows.\r\nA strong portfolio of publications, patents, or significant open-source contributions that demonstrates influence on the broader engineering community.\r\nThe salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.\r\nCandidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.\r\nSalary Range\r\n$240,000 — $330,000 USD\r\nMotional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more.\r\nOur journey is always people first.\r\nWe aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.\r\nWe’re creating first‑of‑its‑kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it’s not only good or business, it’s the right thing to do.\r\nScale up, not starting up.\r\nOur team is behind some of the industry's largest leaps forward, including the first fully‑autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest‑standing public robotaxi fleet. We’re driven to scale; we’re moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.\r\nFormed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter , LinkedIn ,Instagram and YouTube .\r\nMotional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.\r\nMotional is powered by a uniquely talented, highly experienced team with a diverse set of skills across engineering, robotics, machine-learning, and artificial intelligence.#J-18808-Ljbffr","company":"Motional Ad","rawCompany":"motional ad","city":"Brooklyn","state":"NY","isRemote":false,"isActive":true,"createdAt":"2026-09-23T01:13:57.223Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer, Data Mining","description":"Our teams are made up of engineers, researchers, innovators, dreamers, and doers. Together, we can change the world.\r\nAll Motional open positions and applications will be posted here on the official website.\r\nInfrastructurePrincipal Machine Learning Engineer, Data MiningBoston, Las Vegas, Pittsburgh, Remote U.S. Only\r\nAt Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag , our ML-powered multimodal data mining framework, is the engine that powers this discovery. As a Principal Machine Learning Engineer, you will serve as a foundational technical leader shaping the long-term, multi-year vision for our foundation model post-training ecosystem. While training foundation models from scratch is on our horizon, your immediate mandate is to architect the systems that adapt, align, and optimize massive multimodal models for our autonomy stack.\r\nArmed with a strong sense of product, you will ensure our technical investments directly translate into downstream value, accelerating edge-case discovery, reducing engineering costs, and improving the final autonomous driving product. You will tackle highly complex, ambiguous problems, creating clarity and defining objectives that pay future dividends for the entire company. By championing deep cross-team collaboration, you will seamlessly connect ML capabilities with our Autonomy and Infrastructure organizations, breaking down silos to ensure smooth execution. Operating at the highest levels of technical maturity, you will solve the hardest technical challenges that few others can, setting the standard for state-of-the-art model distillation, advanced alignment techniques, automated agentic reasoning workflows, and the ultra-efficient deployment of billion-parameter models.\r\nWhat You'll Do:\r\nSet the Technical Direction for Data Mining:Define the multi-year ML roadmap for our multimodal data-mining platform (Omnitag). Turn complex, ambiguous problems into clear objectives, balancing long-term foundational investments (e.g., agentic pipelines) with short-term tactical goals to drive maximum impact.\r\nBuild the Data Flywheel:Own the full lifecycle of our ML data pipelines to close the active-learning loop. You will align massive multimodal teacher models and distill them into efficient student models for exabyte-scale search, accelerating model error diagnosis and reducing compute costs for automated curation.\r\nArchitect Massive-Scale Systems & Tackle the Hardest Challenges:Design the architecture for applying billion-parameter models to real-world AV logs. As the lead implementer for our toughest technical bottlenecks, you will push the boundaries of parameter-efficient fine-tuning, optimize inference latency for large-scale retrieval, and build RL-driven reasoning systems—all while proactively managing system reliability and cloud footprint.\r\nChampion Cross-Functional Initiatives:Act as the technical bridge between Data Mining, Autonomy, and Infrastructure. Armed with a strong product sense, you will deeply understand the edge cases the autonomy stack needs to solve next and coordinate phased rollouts to seamlessly integrate new discovery capabilities into the core AV development loop.\r\nLead and Grow a High-Performing Pod:Serve as a hands-on player-coach, directly guiding up to 3 engineers. Delegate ownership, coach your team to deliver state-of-the-art implementations, and advocate for tooling and practices that elevate developer productivity and reinforce Motional's culture of engineering excellence.\r\nWhat We're Looking For (Must-Haves):\r\nBS in Computer Science, Machine Learning, or a related field, or equivalent professional experience.\r\n12+ years of hands-on machine learning engineering experience, with a proven track record of owning the end-to-end development cycle of enterprise-scale ML systems, from experiment design through infrastructure, testing, rollout, monitoring, and iteration.\r\nExceptional technical maturity, with a track record of building and shipping impact that is innovative, broad in reach (affecting many teams or orgs), and pays future dividends for the company.\r\nProven ability to solve technical problems that few others can, the person others seek out for complex ML infrastructure, deep learning architectures, and production optimization.\r\nDeep experience training large-scale models from the ground up, including distributed training across multi-node GPU clusters, data pipeline and curation strategy, scaling and evaluation methodology, and the practical debugging of large training runs.\r\nDemonstrated ownership of a technical roadmap for a team or problem area, including balancing competing objectives (impact, quality, engineering time, compute cost) and making deliberate tradeoffs between long-term foundational investment and short-term tactical goals.\r\nAbility to create clarity from ambiguous, complex problems, decomposing them concisely, defining objectives, and establishing measures of progress for yourself and your team.\r\nDeep, generalist ML expertise spanning massive-scale model training, hardware-optimized deployment, and production ML orchestration in cloud environments (AWS, GCP, or Azure).\r\nExperience leading cross-team initiatives, including coordinating phased rollouts and migrations across dependent teams, and mentoring engineers to raise the bar around you.\r\nStrong oral and written communication skills. You can clearly explain complex technical problems using data and analysis, and communicate proposals in a way that earns buy-in and creates alignment.\r\nBonus Points (Nice-to-Haves):\r\nMS/PhD in Computer Science, Machine Learning, or a related field.\r\nExperience as a Tech Lead Manager (TLM) or in direct people management, coaching and growing small teams of 2–3 engineers.\r\nBackground in autonomous driving, robotics, or complex real-time decision-making systems.\r\nExperience with massive-scale ML data mining, multimodal foundation models, and embodied AI.\r\nHands-on experience pretraining or post-training a foundation model, data curation at scale, pretraining or continued-pretraining recipes, SFT/RLHF or other alignment methods, and evaluation harness design.\r\nExperience with model compression and adaptation at scale, knowledge distillation (teacher/student), parameter-efficient fine-tuning, or quantization for high-throughput inference.\r\nExperience with large-scale retrieval or search systems, or RL for reasoning and decision-making.\r\nDeep knowledge of enterprise model serving (TF Serving, Triton, TorchServe) and modern MLOps platforms.\r\nExperience building agentic pipelines or LLM-driven reasoning and tool-use workflows.\r\nA strong portfolio of publications, patents, or significant open-source contributions that demonstrates influence on the broader engineering community.\r\nThe salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.\r\nCandidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.\r\nSalary Range\r\n$240,000 — $330,000 USD\r\nMotional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more.\r\nOur journey is always people first.\r\nWe aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.\r\nWe’re creating first‑of‑its‑kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it’s not only good or business, it’s the right thing to do.\r\nScale up, not starting up.\r\nOur team is behind some of the industry's largest leaps forward, including the first fully‑autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest‑standing public robotaxi fleet. We’re driven to scale; we’re moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.\r\nFormed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter , LinkedIn ,Instagram and YouTube .\r\nMotional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.\r\nMotional is powered by a uniquely talented, highly experienced team with a diverse set of skills across engineering, robotics, machine-learning, and artificial intelligence.#J-18808-Ljbffr","datePosted":"2026-09-23T01:13:57.223Z","dateModified":"2026-09-23T01:13:57.223Z","hiringOrganization":{"@type":"Organization","name":"Motional Ad","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Brooklyn","addressRegion":"NY","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"979fb88ecff107cd83c19ae4"},"url":"https://jobsearcher.com/jobs/979fb88ecff107cd83c19ae4"}}