STEM OPT ML Engineer Jobs
ML Engineer roles qualify for STEM OPT because they fall under computer science and engineering CIP codes, giving you up to 24 months of additional work authorization beyond your initial OPT period. Your employer must be enrolled in E-Verify, and you'll need an approved I-983 training plan tied to a qualifying STEM degree.
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At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard — from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.
As a Senior Machine Learning Engineer on the State Estimation and Mapping (SEAM) organization, you will develop and improve the ML perception model that powers the secondary (fallback) autonomy stack for Super Cruise 3. You will focus on building robust perception from multi-modal camera, lidar, and radar data so the vehicle can safely bring itself to a stop when the primary autonomy stack is unavailable. You will lead the design, implementation, and continuous improvement of ML models for object detection, segmentation, tracking, and prediction, working closely with partner teams across perception, planning, controls, and safety.
- Design, train, and evaluate ML perception models for object detection, semantic/instance segmentation, tracking, and short-horizon prediction using multi-modal camera, lidar, and radar data.
- Develop and maintain the secondary stack perception model that enables the fallback autonomy system to safely bring the vehicle to a minimal risk condition when the primary system experiences a fault.
- Define clear ML success metrics (e.g., precision/recall, latency, robustness under edge cases) and drive systematic experimentation to improve model performance against those metrics.
- Analyze large-scale datasets, curate challenging scenarios, and build data selection and labeling strategies that improve robustness for long-tail and degraded-sensor conditions.
- Implement efficient training and inference pipelines, including model optimization techniques (e.g., pruning, quantization, distillation) to meet on-vehicle compute and latency budgets.
- Collaborate with software and infra engineers to integrate models into production systems, including interfaces, configuration, deployment, monitoring, and regression safeguards.
- Partner with Safety, Systems Engineering, and Product to translate system requirements into concrete ML model requirements, metrics, and validation criteria.
- Contribute to verification and validation strategies for the fallback perception model, including offline evaluation, simulation, hardware-in-the-loop, and on-road testing.
- Participate in code reviews, promote ML and software engineering best practices, and provide technical mentorship to other engineers.
Qualifications
- BS, MS, or PhD in Machine Learning, Robotics, Computer Science, or a related technical field; or equivalent practical experience building ML perception systems.
- 3–5 years of experience developing ML solutions in perception, prediction, and/or autonomous driving or related domains.
- Strong experience with multi-modal sensor data (camera, lidar, radar), including data preprocessing, synchronization, and fusion.
- Deep expertise in modern deep learning for perception, such as convolutional and transformer-based architectures for:
- 2D/3D object detection
- Semantic and instance segmentation
- Multi-object tracking and motion prediction
- Proficiency in at least one major ML framework (e.g., PyTorch, TensorFlow, JAX) and Python for model development, training, and analysis.
- Solid software engineering skills, including experience working in C++ or similar languages in large, collaborative codebases.
- Demonstrated ability to define ML metrics, design experiments, and systematically improve model performance and robustness.
- Strong problem-solving, communication, and cross-functional collaboration skills.
- Self-motivated, with a passion for autonomous driving technology and its potential impact on safety and mobility.
Nice to have
- Experience deploying ML models on embedded or resource-constrained platforms, including model optimization and performance tuning for real-time inference.
- Experience with AV/ADAS perception stacks, robotics, or ROS.
- Familiarity with safety-critical systems and development practices.
- Experience with large-scale data pipelines, labeling workflows, and experiment management for ML.
LOCATION
Remote: This role is based remotely but if you live within a 50-mile radius of Atlanta, Austin, Detroit, Warren, Milford or Mountain View, you are expected to report to that location three times per week, at minimum.
Compensation
The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area.
- The salary range for this role is $170,600.00 to $261,300.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
- Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Benefits
- Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more. This job may be eligible for relocation benefits.
About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
Benefits Overview
From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.
Non-Discrimination and Equal Employment Opportunities (U.S.)
General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.
Accommodations
General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.
Job Description
At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard — from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.
As a Senior Machine Learning Engineer on the State Estimation and Mapping (SEAM) organization, you will develop and improve the ML perception model that powers the secondary (fallback) autonomy stack for Super Cruise 3. You will focus on building robust perception from multi-modal camera, lidar, and radar data so the vehicle can safely bring itself to a stop when the primary autonomy stack is unavailable. You will lead the design, implementation, and continuous improvement of ML models for object detection, segmentation, tracking, and prediction, working closely with partner teams across perception, planning, controls, and safety.
- Design, train, and evaluate ML perception models for object detection, semantic/instance segmentation, tracking, and short-horizon prediction using multi-modal camera, lidar, and radar data.
- Develop and maintain the secondary stack perception model that enables the fallback autonomy system to safely bring the vehicle to a minimal risk condition when the primary system experiences a fault.
- Define clear ML success metrics (e.g., precision/recall, latency, robustness under edge cases) and drive systematic experimentation to improve model performance against those metrics.
- Analyze large-scale datasets, curate challenging scenarios, and build data selection and labeling strategies that improve robustness for long-tail and degraded-sensor conditions.
- Implement efficient training and inference pipelines, including model optimization techniques (e.g., pruning, quantization, distillation) to meet on-vehicle compute and latency budgets.
- Collaborate with software and infra engineers to integrate models into production systems, including interfaces, configuration, deployment, monitoring, and regression safeguards.
- Partner with Safety, Systems Engineering, and Product to translate system requirements into concrete ML model requirements, metrics, and validation criteria.
- Contribute to verification and validation strategies for the fallback perception model, including offline evaluation, simulation, hardware-in-the-loop, and on-road testing.
- Participate in code reviews, promote ML and software engineering best practices, and provide technical mentorship to other engineers.
Qualifications
- BS, MS, or PhD in Machine Learning, Robotics, Computer Science, or a related technical field; or equivalent practical experience building ML perception systems.
- 3–5 years of experience developing ML solutions in perception, prediction, and/or autonomous driving or related domains.
- Strong experience with multi-modal sensor data (camera, lidar, radar), including data preprocessing, synchronization, and fusion.
- Deep expertise in modern deep learning for perception, such as convolutional and transformer-based architectures for:
- 2D/3D object detection
- Semantic and instance segmentation
- Multi-object tracking and motion prediction
- Proficiency in at least one major ML framework (e.g., PyTorch, TensorFlow, JAX) and Python for model development, training, and analysis.
- Solid software engineering skills, including experience working in C++ or similar languages in large, collaborative codebases.
- Demonstrated ability to define ML metrics, design experiments, and systematically improve model performance and robustness.
- Strong problem-solving, communication, and cross-functional collaboration skills.
- Self-motivated, with a passion for autonomous driving technology and its potential impact on safety and mobility.
Nice to have
- Experience deploying ML models on embedded or resource-constrained platforms, including model optimization and performance tuning for real-time inference.
- Experience with AV/ADAS perception stacks, robotics, or ROS.
- Familiarity with safety-critical systems and development practices.
- Experience with large-scale data pipelines, labeling workflows, and experiment management for ML.
LOCATION
Remote: This role is based remotely but if you live within a 50-mile radius of Atlanta, Austin, Detroit, Warren, Milford or Mountain View, you are expected to report to that location three times per week, at minimum.
Compensation
The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area.
- The salary range for this role is $170,600.00 to $261,300.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
- Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Benefits
- Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more. This job may be eligible for relocation benefits.
About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
Benefits Overview
From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.
Non-Discrimination and Equal Employment Opportunities (U.S.)
General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.
Accommodations
General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.
See all 765+ STEM OPT ML Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT ML Engineer Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization as a ML Engineer
Verify your CIP code matches ML Engineering
Check your degree's Classification of Instructional Programs code against the DHS STEM OPT designated degree list before applying. Computer Science (11.0701), Electrical Engineering (14.1001), and Applied Mathematics (27.0301) are common qualifying codes for ML Engineer roles.
Confirm E-Verify enrollment before accepting offers
Ask recruiters for their E-Verify company ID or check enrollment status directly through the E-Verify employer search tool. An employer not enrolled in E-Verify cannot legally support your STEM OPT extension, regardless of how eager they are to hire you.
Use Migrate Mate to filter ML Engineer roles by E-Verify status
Search ML Engineer positions on Migrate Mate to surface employers already verified for STEM OPT eligibility. This cuts the research time of manually cross-referencing job postings against E-Verify enrollment records before you invest in an application.
Build your I-983 training plan around ML deliverables
Draft your I-983 before your offer letter is finalized so your hiring manager can sign off quickly. Map specific ML Engineering tasks, such as model training pipelines and production deployment, to your STEM degree's learning objectives to satisfy USCIS review standards.
Target employers with active H-1B filing history in ML roles
Companies that regularly file H-1B visa petitions for software and ML roles have established immigration infrastructure and understand STEM OPT reporting obligations. DOL LCA disclosure data shows which employers file for ML Engineer-adjacent SOC codes year over year.
Time your STEM OPT application to cover your start date
File your STEM OPT extension with your DSO at least 90 days before your initial OPT expires. USCIS recommends submitting Form I-765 early enough that your EAD arrives before your authorization lapses, protecting your ability to start on your target date.
Frequently Asked Questions
Does an ML Engineer role qualify for the STEM OPT extension?
ML Engineer positions typically qualify when your employer maps the role to a STEM-designated SOC code, such as Software Developers (15-1252) or Computer and Information Research Scientists (15-1221), and your degree falls under a qualifying CIP code. Confirm the match with your DSO before filing. You can verify the SOC classification for ML Engineering work through O*NET.
What STEM degrees are accepted for an ML Engineer STEM OPT extension?
Degrees in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, and Data Science are commonly accepted, provided they appear on the DHS STEM Designated Degree Program list under their respective CIP codes. A degree in a non-STEM field does not qualify even if your coursework included machine learning. Your DSO can confirm your specific CIP code eligibility before you apply.
How do I verify that an ML Engineer employer is enrolled in E-Verify?
Use the E-Verify employer search tool to look up any company by name before accepting an offer. Enrollment in E-Verify is a legal requirement for STEM OPT employers, not an optional benefit. If a company is not enrolled, they cannot legally employ you under the STEM OPT extension. Migrate Mate surfaces ML Engineer roles from E-Verify-enrolled employers so you can focus your search efficiently.
What goes into an I-983 training plan for an ML Engineer position?
Your I-983 must describe how the ML Engineer role provides practical training related to your STEM degree. Include specific responsibilities such as developing neural network architectures, running model validation pipelines, or deploying inference systems, and explain how each connects to your academic coursework. Both you and your employer's authorized representative must sign it, and your DSO must review and maintain it throughout your extension period.
Does cap-gap protection apply if my H-1B is selected while I work as an ML Engineer on STEM OPT?
Yes. If your employer files an H-1B petition on your behalf before your STEM OPT EAD expires, cap-gap protection automatically extends your work authorization through September 30 of that fiscal year, or until your H-1B start date of October 1, whichever comes first. You can continue working as an ML Engineer without interruption as long as the petition remains pending or approved. USCIS provides formal guidance on cap-gap eligibility on its website.