Senior, Machine Learning Engineer - End-to-End

About the Company

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.

A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.

Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.

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 role focuses on owning meaningful portions of the E2E stack, improving model performance at scale, and driving iteration through data, experimentation, and cross-functional collaboration.

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: For this position, 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.

Perks of Being a Full-time Torc’r

Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:

A competitive compensation package that includes a bonus component and stock options

100% paid medical, dental, and vision premiums for full-time employees

401K plan with a 6% employer matchFlexibility in schedule and generous paid vacation (available immediately after start date)Company-wide holiday office closures

AD+D and Life Insurance

At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs 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.

Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.

Job ID: 102665

Hiring Range for Job Opening

US Pay Range

$226,400 - $271,700 USD