Senior Machine Learning Engineer (Multimodal Perception)

• Autonomy MLE role focused on bridging perception and planning to develop and release robust learned driving policies. The primary objective of this role is to train, evaluate, and transition production-ready decision-making models into real-world autonomous navigation systems
• In this hybrid role, you will report to the Technical Lead Manager of the Special Vehicle Compliance team
• Develop, evaluate, and release learned driving policies for complex navigation and yielding scenarios
• Work cross-functionally at the intersection of perception and planning, translating multi-modal perception outputs into robust behavioral actions
• Deploy learned models into closed-loop simulation environments, benchmark against strict safety metrics, and drive the transition of these models into production releases
• Advance the transition from rule-based heuristics to scalable, data-driven learned policies

Benefits

• Medical, dental, and vision insurance for employees and dependents
• Employee assistance programs focused on mental health
• Personalized workplace adjustments for diverse needs and abilities, including physical, mental, and neurodivergent considerations
• Access to mental health apps
• Onsite wellness centers
• Medical advocacy program for transgender employees
• Second medical opinion for you and your loved ones
• Counseling services
• Support programs including menopause benefit
• Competitive compensation
• Regular bonus and equity performance grant opportunities
• Generous 401(k) and regional retirement plans
• Annual cross-company compensation review and pay equity analysis
• 1-on-1 financial coaching
• Fertility and growing family assistance
• Parental leave and baby bonding leave
• Elder care and support
• Backup childcare
• Survivor income benefit
• Caregiver leave
• Paid time off, including vacation, bereavement, sick leave, parental leave, disability, and holidays
• Jury duty leave
• Military leave
• Hybrid work model with remote work opportunities also available
• Educational reimbursement
• Peer learning and coaching platform
• Donation matching programs
• Employee resource groups
• Volunteer hours
• Internal community groups and local culture clubs
• Inspiring spaces to work, recharge, and collaborate with fellow Waymonauts
• On-site meals and snacks
• Fitness centers, massage programs, and ergonomic support
• On-demand fitness, wellbeing, and cooking classes
• Commuter benefits- Hands-on experience working across both perception and planning stacks. Proficiency in learned driving policies (RL / imitation learning), PyTorch / JAX, closed-loop simulator evaluation, and a track record of releasing models to production
• 2–5+ years experience training and releasing ML models in autonomous driving, robotics, or complex spatial AI
• Familiarity with Vision-Language-Action (VLA) models and World Models is a strong plus
• Experience using foundation models and AI tools for scenario generation, evaluation analysis, and rapid experimentation