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Torc RoboticsTR

Staff, ML Engineer - E2E

Torc Robotics, an independent subsidiary of Daimler Truck AG, is a pioneer in autonomous driving technology, currently focused on commercializing self-driving trucks for long-haul applications in the U.S. Founded in 2005, Torc has extensive experience in developing safety-critical, self-driving solutions.

Torc Robotics

Employee count: 501-1000

Salary: 220k-330k USD

United States only

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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 Staff Machine Learning Engineer focused on End-to-End (E2E) Model Development, you will lead the design and deployment of learning-based architectures that connect perception inputs to driving decisions — advancing the frontier of closed-loop autonomous driving performance.

You’ll architect and push forward Torc’s End – to – End approaches through unified, differentiable pipelines, leveraging massive real-world and simulated datasets to continuously improve system intelligence.

This is a high-impact technical leadership role focused on core model research and large-scale ML development, not feature-layer logic or rule-based planning.

What You’ll Do

  • Lead E2E model design and development — define architectures that directly map multi-modal sensor inputs (camera, LiDAR, radar, HD maps) to mid- or high-level driving actions or cost functions.
  • Drive large-scale training and evaluation for E2E learning, integrating data from perception, behavior prediction, and control systems.
  • Develop and refine learning objectives that align with real-world driving metrics: safety, comfort, compliance, and efficiency.
  • Architect scalable pipelines for multi-task, multi-modal learning, leveraging both real-world and synthetic data.
  • Prototype and evaluate new paradigms such as differentiable planning, imitation learning, reinforcement learning, and world models for AV behavior.
  • Collaborate cross-functionally with Perception, Prediction, and Motion Planning teams to align interfaces and ensure consistency between learned and modular components.
  • Establish robust evaluation frameworks for E2E performance, including closed-loop simulation and on-road validation.
  • Mentor engineers and scientists in large-scale experimentation, model interpretability, and data-driven debugging.
  • Stay at the frontier of ML research, exploring advancements in foundation models, sequence modeling, self-supervision, and generative world representations.

What You’ll Need to Succeed

  • 10+ years of experience developing deep learning systems for perception, planning, or control.
  • M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or related field (or equivalent practical experience).
  • Deep expertise in multi-modal ML, sequence modeling, or policy learning (e.g., Transformers, diffusion models, imitation learning).
  • Proven track record in large-scale model training and optimization for real-world tasks.
  • Strong proficiency in Python, PyTorch, or TensorFlow, and experience with distributed ML frameworks.
  • Solid understanding of sensor fusion, spatiotemporal modeling, and vehicle dynamics.
  • Demonstrated leadership in driving technical roadmaps, mentoring teams, and delivering production-quality ML solutions.
  • Experience using Ray

Bonus Points!

  • Experience developing E2E or mid-to-end models for autonomous driving, ADAS, or robotics.
  • Familiarity with differentiable cost maps, latent space planning, or behavior cloning / reinforcement learning in driving domains.
  • Hands-on experience with simulation-in-the-loop training and evaluation.
  • Understanding of safety validation and interpretability for learned driving systems.
  • Publications or open-source contributions in top-tier ML or robotics venues (CVPR, NeurIPS, ICLR, ICRA, CoRL).
  • Experience with foundation models or large-scale multimodal pretraining for perception and planning

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 match
  • Flexibility 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.

US Pay Range:

$219,700.00 - $329,600.00

Job ID: 102406

About the job

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Job type

Full Time

Experience level

Mid-level

Salary

Salary: 220k-330k USD

Location requirements

Hiring timezones

United States +/- 0 hours

About Torc Robotics

Learn more about Torc Robotics and their company culture.

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What began in 2005 as Torc Technologies, a venture by a group of Virginia Tech graduate students, has evolved into a leading name in autonomous vehicle technology. The mission from the outset was to continue their collegiate work on autonomous vehicle software, initially focusing on Tele-Operated Robotic Controls (TORC) and developing Level 4 autonomous technology. A significant early milestone came in 2007 when Torc, in partnership with Virginia Tech, secured third place in the DARPA Urban Challenge. This achievement involved their Ford Escape, 'Odin,' autonomously navigating 60 miles of urban and off-road environments.

The company's journey continued with impactful projects, including a 2010 partnership with Virginia Tech for the National Federation of the Blind's Blind Driver Challenge, which earned them the National Instruments' 2010 Application of the Year. This project saw a blind driver independently operate Torc's modified Ford Escape on the Daytona Speedway in 2011. Torc's expertise also extended to defense, developing autonomous solutions like the Ground Unmanned Support Surrogate (GUSS) to assist military personnel. Over the years, Torc has been involved in various defense and heavy equipment applications, and participated in the DARPA Robotics Challenge. A pivotal moment arrived in March 2019 when Daimler AG, through Daimler Trucks North America, acquired a majority stake in Torc Robotics. This partnership shifted Torc's primary focus to commercializing autonomous trucks for long-haul applications in the United States. Torc is now an independent subsidiary of Daimler Truck AG. The company has since expanded its operations, opening an engineering office in Austin, Texas, and a Technology and Development Center in Stuttgart, Germany in 2022, as well as facilities in Albuquerque, New Mexico, and Montreal, Canada. Torc continues to advance its 'physical AI,' enabling self-driving trucks to perceive, understand, and act in the real world, with a commercial launch targeted for 2027.

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