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Senior, Machine Learning Engineer - End-to-End Remote - U.S, Ann Arbor, MI
Torc Robotics, Inc.
- Ann Arbor, Michigan, United States
- Ann Arbor, Michigan, United States
Über
Meet the Team As a Senior Machine Learning Engineer – End-to-End (E2E), you will develop and scale learning‑based systems that connect multi‑modal perception inputs to driving behavior, enabling safe, efficient, and human‑like autonomy for real‑world freight operations. You’ll work at the intersection of perception, prediction, and planning, contributing to unified learning pipelines that operate in closed‑loop environments. This is a hands‑on engineering role focused on execution, iteration, and delivery.
What You’ll Do
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
What You’ll Need to Succeed
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, with ability to write production‑quality ML code
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
Bonus Points
Experience developing End‑to‑End or mid‑to‑end models for autonomous driving or robotics
Experience with vision‑language models (VLMs) or vision‑language‑action (VLA) systems
Familiarity with closed‑loop simulation and evaluation frameworks
Experience with reinforcement learning or imitation learning in real‑world systems
Experience with distributed training frameworks (e.g., Ray)
Understanding of vehicle dynamics, motion planning, or multi‑agent systems
Work Location We are open to hiring in Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States.
Benefits
A competitive compensation package that includes a bonus component and stock options
100% paid medical, dental, and vision premiums for full‑time employees
401(k) plan with a 6% employer match
Flexibility in schedule and generous paid vacation (available immediately after start date)
Company‑wide holiday office closures
AD&D and Life Insurance
EEO Torc is committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our team and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities. Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply.
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Sprachkenntnisse
- English
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