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Torc RoboticsTR

Staff, ML Engineer - Road & Lane Detection

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: 209k-314k USD

Canada 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 Road Lane Detection, you will lead the model development efforts that enable Torc’s autonomous vehicles to perceive and interpret road geometry, lane structures, and drivable surfaces with precision and robustness.

You’ll define the next generation of deep learning architectures and data-driven approaches that extract high-fidelity road and lane semantics from multi-modal sensor data — driving critical improvements in perception accuracy, stability, and scalability.

This is a technical leadership role focused on model innovation and maturity, not downstream feature integration.

What You’ll Do

  • Own the model roadmap for Road Lane Detection within the Model Dev ML org — from concept through production-grade model maturity.

  • Research, design, and train advanced neural architectures (e.g., multi-camera BEV transformers, LiDAR-vision fusion models, topological lane graph networks) to detect, segment, and model road structures and lane connectivity.

  • Lead data strategy for this domain — defining data curation, labeling policies, and active learning pipelines to capture long-tail scenarios (e.g., occlusions, complex merges, construction zones).

  • Develop robust metrics and evaluation frameworks for lane and road geometry accuracy, temporal consistency, and cross-domain generalization.

  • Advance foundational capabilities such as self-supervised pretraining, synthetic-to-real adaptation, and temporal modeling for road and lane understanding.

  • Drive large-scale experiments — designing, running, and analyzing results from distributed training workflows and ablations to identify scalable improvements.

  • Collaborate with other model dev/perception teams to ensure model coherence and interface consistency.

  • Mentor engineers and scientists, setting best practices for model training, evaluation, and code quality.

  • Stay ahead of the research frontier by evaluating and adapting emerging techniques (e.g., BEV-based large models, vectorized map prediction, lane graph transformers) to production-grade perception.

What You’ll Need to Succeed

  • 10+ years of experience developing deep learning models for perception or computer vision at scale.
  • M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related field (or equivalent experience).

  • Deep expertise in semantic and instance segmentation, BEV modeling, or scene topology estimation.

  • Strong understanding of lane and road geometry modeling, camera calibration, and sensor projection.

  • Proficiency with Python and modern ML frameworks (e.g., PyTorch, Lightning).

  • Experience with distributed training pipelines, experiment management, and large-scale dataset handling.

  • Proven leadership in guiding technical roadmaps, mentoring engineers, and driving measurable model improvements.

Bonus Points!

  • Experience developing ML models for autonomous driving, mapping, or ADAS systems.

  • Familiarity with multi-modal fusion (camera, LiDAR, radar, HD maps).

  • Hands-on experience with BEV-based and topological prediction models.

  • Contributions to perception-related ML research (CVPR, NeurIPS, ICCV, ICLR, ICRA).

  • Strong intuition for data quality, bias mitigation, and uncertainty modeling.

Perks of Being a Full-time Torc’r (Canada)

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
  • Medical, dental, and vision for full-time employees
  • RRSP plan with a 4% employer match
  • Public Transit Subsidy (Montreal area only)
  • Flexibility in schedule and generous paid vacation
  • Company-wide holiday office closures
  • 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.

Hiring Range for Job Opening 

CAD Compensation Range:

$209,300-313,800 CAD

Job ID: R-102402

About the job

Apply before

Posted on

Job type

Full Time

Experience level

Mid-level

Salary

Salary: 209k-314k USD

Location requirements

Hiring timezones

Canada +/- 0 hours

About Torc Robotics

Learn more about Torc Robotics and their company culture.

View company profile

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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Torc Robotics hiring Staff, ML Engineer - Road & Lane Detection • Remote (Work from Home) | Himalayas