Machine Learning Visa Sponsorship Jobs in Massachusetts
Massachusetts is one of the strongest states for machine learning visa sponsorship, anchored by tech and biotech employers in Greater Boston, Cambridge, and the Route 128 corridor. Companies like Google, Microsoft, Amazon, and IBM have significant ML operations here, alongside AI-focused startups and research institutions including MIT and Harvard that fuel a deep local talent pipeline.
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About Motional:
Motional is a public transit and autonomous vehicle pioneer, developing Level 4 driverless vehicles that are changing the way the world moves. At the heart of our mission is the Autonomy organization, where we solve some of the most complex engineering and artificial intelligence challenges of our generation.
Mission Summary:
Motional is seeking a visionary, technically deep Director of Behaviors to lead our machine learning-based Prediction and Planning teams. In this role, you will sit at the intersection of intent forecasting and ego-vehicle decision-making. You will be directly responsible for leading multiple engineering sub-teams, setting the technical roadmap for our next-generation behavior stack, and pioneering the shift toward state-of-the-art end-to-end models that execute joint prediction and planning.
As a senior leader in the Autonomy organization, you will not only drive technical breakthroughs but will also scale and nurture a world-class AI organization in a sustainable, inclusive, and highly collaborative fashion.
Core Responsibilities:
- Strategic Leadership: Oversee and unify the machine learning-based Prediction and Motion Planning teams. Establish a clear, aggressive, yet sustainable technical roadmap that transitions our stack towards a unified (fully learnt) Large Driving Model performing joint prediction and planning.
- Technical Direction: Stay at the absolute frontier of AI research and define the technical roadmap for developing state-of-the-art imitation learning (IL) and reinforcement learning (RL) approaches to advance end-to-end learnt planning. Guide the team in exploring and incorporating modern paradigms like Vision-Language-Action models (VLAs) to improve the vehicle's semantic understanding, reasoning, and zero-shot generalization capabilities in complex urban environments.
- Organizational Growth: Lead, mentor, and scale multiple sub-teams of machine learning engineers and researchers. Implement sustainable engineering practices that prevent burnout, promote psychological safety, and ensure high technical velocity.
- Publish: As part of this role, you will also be expected to publish stellar work in conferences like CVPR, ICCV, ECCV and Neurips.
- Cross-Functional Collaboration: Partner closely with Perception, Infrastructure and Systems Engineering to ensure the Large Driving Model seamlessly integrates onto the vehicle platform and meets rigorous safety and real-time performance standards.
Required Qualifications & Experience:
- Proven Leadership: 5+ years of experience managing high-performing engineering teams, with at least 3+ years of experience managing multiple sub-teams within an autonomous systems, robotics, or advanced AI organization.
- Sustainable Scaling: Demonstrated track record of growing an engineering organization sustainably—balancing technical debt, architectural scalability, and team well-being.
- ML Behavior Expertise: Deep theoretical and practical proficiency in machine learning applied to robotics behaviors. Advanced expertise in Imitation Learning and Reinforcement Learning for decision-making. Strong understanding of the full lifecycle from research to vehicle deployment.
- Unified Architectures: Proven experience guiding teams toward building integrated models (e.g., trajectory forecasting joint with ego-policy generation) rather than decoupled, sequential pipelines.
- Modern AI Paradigms: Strong familiarity with multimodal foundational AI models, specifically Vision-Language-Action models (VLAs).
- Educational Background: M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related quantitative field with a heavy focus on Machine Learning.
Preferred Qualifications:
- Experience building and scaling up LLMs/VLMs/VLAs and successfully deploying to production.
- A strong footprint in the AI/robotics research community (CVPR, ICCV, NeurIPS, ICRA, IROS publications).
- Experience building large-scale data pipelines and training infrastructure required to train large driving models.
Work Arrangement:
We encourage a hybrid schedule with in-office time at one of our locations in Boston or Pittsburgh to support collaboration, or this role can be fully remote.
Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We're driven by something more.
Our journey is always people first.
We 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.
Higher purpose, greater impact.
We'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 for our business, it's the right thing to do.
Scale up, not starting up.
Our 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.
Formed 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.
Motional 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.
Machine Learning Job Roles in Massachusetts
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Search Machine Learning Jobs in MassachusettsMachine Learning Jobs in Massachusetts: Frequently Asked Questions
Which companies sponsor visas for machine learning roles in Massachusetts?
Major sponsors for machine learning roles in Massachusetts include Google, Amazon, Microsoft, IBM, and Meta, all of which have substantial engineering presence in the Greater Boston area. Biotech and life sciences companies such as Biogen and Moderna also hire ML engineers for research applications. Beyond large employers, AI-focused startups in Cambridge and Boston's Seaport District are active sponsors, particularly for senior and specialized ML positions.
Which visa types are most common for machine learning roles in Massachusetts?
The H-1B visa is the most common visa for machine learning professionals in Massachusetts, as ML engineer and research scientist roles typically qualify as specialty occupations requiring at least a bachelor's degree in computer science, mathematics, or a related field. Candidates with exceptional publication records or industry recognition may qualify for the O-1A. Some researchers enter through J-1 visa exchange visitor programs tied to MIT, Harvard, or other institutions before transitioning to employer-sponsored status.
Which cities in Massachusetts have the most machine learning sponsorship jobs?
Cambridge and Boston together account for the majority of machine learning sponsorship jobs in Massachusetts, driven by proximity to MIT, Harvard, and a dense concentration of AI research labs and tech employers. The Route 128 corridor, including Waltham, Burlington, and Lexington, hosts established enterprise tech companies with regular ML hiring. Worcester has a smaller but growing presence tied to WPI and regional healthcare technology employers.
How to find machine learning visa sponsorship jobs in Massachusetts?
Migrate Mate is built specifically for international job seekers and filters machine learning roles in Massachusetts by visa sponsorship availability, saving you from manually screening thousands of listings. The platform surfaces employers with verified sponsorship history across Greater Boston, Cambridge, and the Route 128 corridor. Because ML hiring in Massachusetts spans large tech firms, biotech companies, and AI startups, using a focused tool like Migrate Mate helps you target roles where sponsorship is a realistic expectation.
Are there any state-specific considerations for machine learning visa sponsorship in Massachusetts?
Massachusetts employers sponsoring H-1B workers must pay at least the prevailing wage for the specific ML role and location, which is determined by Department of Labor data and tends to reflect the state's competitive compensation environment. The concentration of research universities in Massachusetts also means many ML professionals enter the workforce through OPT or STEM OPT extensions before securing employer sponsorship, making early engagement with potential sponsors during academic programs a practical consideration.
What is the prevailing wage for sponsored machine learning jobs in Massachusetts?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.