Sr. Machine Learning Engineer, Autonomy

About the Role

• We're building a new autonomous driving organization to deliver production-ready L4 autonomy across trucks, buses, passenger vehicles, and robotaxis.
• Our approach is ML-first, centered around end-to-end learning, foundation models, VLA models, and world models.
• As a founding senior engineer, you'll make the architecture decisions most autonomy teams made years ago, then personally drive their implementation into production.
• We are looking for builders, not spectators.
• You'll lead major technical initiatives from ambiguous problems to deployed systems running on real vehicles while helping shape the future of the organization.

Founding Team Opportunity

Most autonomy programs were started years ago. The major architectural decisions and engineering culture were established long before today's engineers joined.

We're assembling the founding team that will define and build our autonomy platform.

The engineers who join now will have outsized influence on architecture, technical roadmap, engineering culture, hiring standards, and future direction.

Responsibilities

• Lead development of end-to-end driving, VLA, or world model systems.
• Define and implement scalable autonomy architectures.
• Adapt foundation models for autonomous driving.
• Drive major technical initiatives from concept to deployment.
• Improve training, evaluation, and data efficiency.
• Mentor engineers and contribute to team growth.

Qualifications

• Demonstrated grit, ownership, and a track record of driving difficult technical problems from ambiguity to successful deployment.
• Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field.
• 5+ years of experience building ML systems.
• Proven track record of shipping production ML systems.
• Experience leading technical projects from concept to deployment.
• Strong Python and PyTorch (or JAX) skills.

Preferred Qualifications

• Autonomous driving or robotics experience.
• End-to-end driving, VLA/VLM models, world models, or foundation models.
• Large-scale distributed training.
• Simulation, synthetic data, or safety-critical systems.
• Publications at top conferences.

Interview Process

• Application Review - Coding Test - 1st interview - 2nd interview - Offer Negotiation - Hiring
• The screening procedures may vary depending on the position, schedule, or other circumstances.

Additional information

You will be individually notified of the screening schedule and results via the email address provided in your application.

Compensation

• $210,000 - $300,000

Additional Information

• In accordance with fair hiring practices, do not include any personal information unrelated to your job qualifications (e.g., Social Security Number, family relations, marital status, age, photo, physical condition, place of birth, etc.) in your resume.
• All documents must be submitted in PDF format and under 30MB in size.
• We strongly encourage applications from U.S. veterans and candidates eligible for employment preference under applicable laws.
• Qualified individuals with disabilities are encouraged to apply and will receive consideration under the Americans with Disabilities Act (ADA).
• 42dot does not accept unsolicited resumes and will not pay fees for any such submissions. Equal Opportunity Statement
• 42dot is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.

Please review the following information before applying.

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