Senior Machine Learning Engineer - End-to-End
New
T
Torc RoboticsAutonomous Vehicles
U.SFull-TimeSenior
Salary226400 - 271700 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- Bachelor’s degree with 6+ years, Master’s with 4+ years, or PhD with 0–2 years of experience
- Required Skills
- PythonPyTorch
Requirements
- Bachelor’s degree with 6+ years, Master’s with 4+ years, or PhD with 0–2 years of experience in Machine Learning, Robotics, Computer Science, or a related field with a track record of publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, CoRL)
- Experience developing and deploying ML models for autonomous systems, robotics, or complex decision-making environments
- Strong programming skills in Python and PyTorch
- Experience training and evaluating models using large-scale datasets and distributed compute environments
- Solid understanding of ML architectures used in E2E systems, such as Transformers, BEV models, VLA/VLM approaches, or diffusion models
- Proven ability to debug model behavior, analyze performance metrics, and drive iterative improvements
- Experience contributing to or influencing model architecture and training strategies
- Ability to work cross-functionally and integrate ML systems into larger autonomy pipelines
Responsibilities
- Own development and delivery of End-to-End ML models that map multi-modal sensor inputs (camera, LiDAR, radar, maps) to driving-relevant outputs (trajectories, cost functions, or intermediate representations)
- Train and evaluate models using large-scale datasets from fleet logs, simulation, and synthetic data
- Analyze model performance, identify failure modes, and drive data-driven improvements in robustness and generalization
- Design and refine training pipelines, data workflows, and evaluation strategies to improve iteration speed and model quality
- Contribute to model architecture decisions, including approaches such as imitation learning, reinforcement learning, transformers, and vision-language-action (VLA) models
- Collaborate closely with Perception, Prediction, Planning, and Simulation teams to ensure alignment across the autonomy stack
- Support integration of E2E models into simulation and on-vehicle systems for closed-loop validation
- Improve tooling, experimentation workflows, and reproducibility across the team
- Mentor junior engineers and contribute to team-level best practices and technical discussions
View Full Description & ApplyYou'll be redirected to the employer's site
