Torc Robotics

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. <a href="https://torc.ai/daimler-testing-automated-trucks-public/" rel="noopener noreferrer ugc" target="_blank">Now a part of the Daimler family</a>, 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
Accurate and highly available information about other actors and objects is fundamental to the safe operation of autonomous trucks. Core capabilities depend on accurate tracking estimates to ensure safe and efficient vehicle behavior.
The Tracking Team develops the ML models, state estimation algorithms, and production software responsible for associating and estimating the kinematics of other actors and objects in real time. Our solutions fuse information from multiple sensors and maintain robust performance despite sensor imperfections, environmental challenges, and system degradation. As part of this team, you will develop and deploy production-ready tracking solutions and help solve the challenges of bringing autonomous vehicle technology to real-world commercial applications.
What You'll Do 
<ul>
<li>Design, develop, and deploy production ML models for multi-object tracking, including association, learned pose and kinematic estimation, and sensor fusion using camera, LiDAR, radar, and other vehicle sensors.  </li>
</ul>
<ul>
<li>Develop scalable training and evaluation workflows using PyTorch, distributed training infrastructure, and large-scale real-world datasets.  </li>
</ul>
<ul>
<li>Design and improve tracking and sensor fusion algorithms for robust vehicle pose and kinematics </li>
</ul>
<ul>
<li>Analyze large-scale vehicle data to characterize performance, identify failure modes, and drive model and system improvements.  </li>
</ul>
<ul>
<li>Develop robust, efficient production software in modern C++ and Python across the full development lifecycle.  </li>
</ul>
<ul>
<li>Define evaluation, verification, and validation strategies to ensure Tracking quality, robustness, and safety across diverse operating conditions.  </li>
</ul>
<ul>
<li>Make technical design and architecture decisions, balancing model performance, computational efficiency, robustness, and production constraints.  </li>
</ul>
<ul>
<li>Collaborate with perception, mapping, planning, controls, and platform teams to deliver integrated autonomous driving capabilities.  </li>
</ul>
<ul>
<li>Provide technical leadership through design reviews, code reviews, mentoring, and development of engineering best practices.  </li>
</ul>
 What You'll Need to Succeed 
<ul>
<li>Bachelor’s degree in Computer Science, Software Engineering, Robotics, or a related field with 6+ years of relevant industry experience, or a Master’s degree with 3+ years of relevant industry experience, or a PhD with 1+ year of relevant industry experience.  </li>
</ul>
<ul>
<li>Experience with AV or robotics perception systems (tracking, detection, SLAM, scene modeling, ect.).  </li>
</ul>
<ul>
<li>Strong experience developing and deploying ML models for perception, localization, or sensor fusion domains.   </li>
</ul>
<ul>
<li>Proficiency with PyTorch and modern ML tooling for training, inference, and optimization.   </li>
</ul>
<ul>
<li>Solid understanding of 3D geometry, probabilistic estimation, coordinate transforms, and robotics fundamentals.   </li>
</ul>
<ul>
<li>Demonstrated ability to work with large multimodal datasets and build scalable pipelines for processing, labeling, and evaluation.  </li>
</ul>
<ul>
<li>Strong software engineering fundamentals in Python and C++, including algorithms, data structures, testing, debugging, and performance optimization.  </li>
</ul>
<ul>
<li>Strong written and verbal communication skills and the ability to work effectively on cross-functional teams.  </li>
</ul>
 Bonus Points 
<ul>
<li>Experience with state estimation techniques such as factor graphs, Kalman filtering, nonlinear optimization, or related probabilistic estimation methods.  </li>
</ul>
<ul>
<li>Familiarity with distributed computing tools such as Ray, Kubernetes, or similar orchestration frameworks.   </li>
</ul>
<ul>
<li>Knowledge of embedded and real-time constraints for on-vehicle deployment.   </li>
</ul>
<ul>
<li>Experience in simulation, synthetic data generation, and uncertainty-aware ML modeling.   </li>
</ul>
<ul>
<li>Contributions to open-source robotics, perception, or ML frameworks.   </li>
<li>Familiarity with functional safety standards and automotive development processes, including ISO 26262. </li>
</ul>
 
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:   
<ul>
<li>A competitive compensation package that includes a bonus component and stock options </li>
</ul>
<ul>
<li>100% paid medical, dental, and vision premiums for full-time employees </li>
</ul>
<ul>
<li>401K plan with a 6% employer match </li>
</ul>
<ul>
<li>Flexibility in schedule and generous paid vacation (available immediately after start date) </li>
</ul>
<ul>
<li>AD+D and Life Insurance </li>
</ul>
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: 102957<div><div><div>Hiring Range for Job Opening </div><div>US Pay Range</div><div>$177,300—$212,800 USD</div></div></div>

Senior, ML Engineer - Tracking

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. <a href="https://torc.ai/daimler-testing-automated-trucks-public/" rel="noopener noreferrer ugc" target="_blank">Now a part of the Daimler family</a>, 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 Machine Learning Engineer II – Learned Behaviors, you will help develop and deploy  behavior models that power decision-making for autonomous trucks. Working closely with teams across perception, prediction, planning, and safety, you will contribute to learned behavior modules that enable safe, efficient, and human-like driving in real-world freight operations.    This role focuses on building, validating, and improving machine learning models and infrastructure that support learned behavior systems within the autonomy stack.    What You’ll Do 
<ul>
<li>Develop and train machine learning models for learned behavior systems, including approaches such as behavior cloning, imitation learning, and reinforcement learning.</li>
<li>Implement production-quality ML code to support model training, evaluation, and inference within the autonomy stack.</li>
<li>Analyze model performance, identify failure modes, and propose improvements to increase robustness and generalization across scenarios.</li>
<li>Contribute to model training pipelines and data workflows, curating behavior datasets from simulation, fleet logs, and on-vehicle data.</li>
<li>Collaborate with simulation, validation, and autonomy engineering teams to test and evaluate learned behavior models across diverse driving environments.</li>
<li>Help integrate learned behavior models into simulation and testing workflows, enabling faster iteration and more comprehensive validation.</li>
<li>Support the development of tooling and infrastructure that improves experimentation speed, reproducibility, and model iteration.</li>
<li>Contribute to technical discussions around model architecture and training strategies within the team. </li>
</ul>
What You’ll Need to Succeed 
<ul>
<li>Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 4+ years of industry experience, or a Master’s degree with 2+ years of experience. </li>
<li>Experience applying machine learning techniques such as imitation learning, reinforcement learning, or sequence modeling to robotics, autonomous systems, or complex control environments.</li>
<li>Strong programming skills in Python and PyTorch, with experience writing production-quality ML code.</li>
<li>Experience training and evaluating machine learning models using large datasets and scalable compute environments.</li>
<li>Understanding of ML architectures used in autonomy systems, such as transformers, graph neural networks, or sequence models.</li>
<li>Experience debugging model behavior, analyzing performance metrics, and iterating on training pipelines.</li>
<li>Ability to collaborate with cross-functional teams to integrate ML models into larger software systems. </li>
</ul>
Bonus Points! 
<ul>
<li>Experience working in autonomous driving, robotics, or simulation-based training environments.</li>
<li>Experience with reinforcement learning frameworks or distributed training systems (e.g., Ray).</li>
<li>Experience working with simulation environments or large-scale behavior datasets.</li>
<li>Familiarity with vehicle dynamics, motion planning, or multi-agent decision-making systems.</li>
<li>Experience deploying ML models into production or real-world robotics systems. </li>
</ul>
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:     
<ul>
<li>A competitive compensation package that includes a bonus component and stock options</li>
<li>100% paid medical, dental, and vision premiums for full-time employees</li>
<li>401K plan with a 6% employer match</li>
<li>Flexibility in schedule and generous paid vacation (available immediately after start date)</li>
<li>AD+D and Life Insurance </li>
</ul>
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. 
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.
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:  103006<div><div><div>Hiring Range for Job Opening </div><div>US Pay Range</div><div>$153,200—$183,800 USD</div></div></div>

Machine Learning Engineer II - Learned Planning (Reinforcement Learning)

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. <a href="https://torc.ai/daimler-testing-automated-trucks-public/" rel="noopener noreferrer ugc" target="_blank">Now a part of the Daimler family</a>, 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 – Camera Models, you will develop and deploy machine learning models that power camera-based perception for autonomous trucks. The Camera Models team builds and maintains core vision systems that enable the autonomy stack to understand the environment, detect and localize objects, and estimate scene structure from camera data.    Working closely with teams across perception, data, and infrastructure, you will own the development and improvement of robust, scalable camera-based models that support safe and reliable autonomous driving in real-world freight environments.  This role focuses on owning model development for scoped problem areas, improving system performance through iteration, and delivering production-ready machine learning solutions within the autonomy stack.    What You’ll Do 
<ul>
<li>Design, develop, and deploy deep learning models for camera-based perception (e.g., object detection, segmentation, depth estimation, scene understanding)</li>
<li>Own end-to-end model development for scoped areas, from data curation and training to evaluation and deployment</li>
<li>Write production-quality ML code to support scalable training, evaluation, and inference pipelines</li>
<li>Analyze model performance across diverse driving scenarios, identify failure modes, and improve robustness and generalization</li>
<li>Contribute to and improve large-scale training pipelines, including dataset preparation, distributed training, and experiment tracking</li>
<li>Partner with data teams to improve dataset quality, including labeling strategies and coverage of edge cases</li>
<li>Collaborate with perception, simulation, and validation teams to evaluate and integrate models into the autonomy stack</li>
<li>Improve tooling, workflows, and infrastructure to accelerate experimentation and model iteration</li>
<li>Contribute to model architecture decisions and technical discussions within the team</li>
<li>Mentor junior engineers on implementation, debugging, and best practices </li>
</ul>
What You’ll Need to Succeed 
<ul>
<li>Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 6+ years of industry experience, OR Master’s degree with 3+ years OR PhD with 1+ years of experience</li>
<li>Experience developing and deploying deep learning models for computer vision or perception systems</li>
<li>Strong programming skills in Python and PyTorch, with experience writing production-quality ML code</li>
<li>Experience training and evaluating models using large-scale datasets and distributed compute environments</li>
<li>Solid understanding of modern deep learning architectures used in perception (e.g., CNNs, transformers, multi-task models)</li>
<li>Experience debugging model behavior, analyzing performance metrics, and improving model reliability</li>
<li>Ability to translate ambiguous problems into structured ML solutions and deliver independently</li>
<li>Experience collaborating cross-functionally to integrate ML models into larger autonomy or robotics systems </li>
</ul>
 Bonus Points: 
<ul>
<li>Experience in autonomous driving, robotics, or simulation-based ML systems</li>
<li>Experience with multi-task learning or unified perception architectures</li>
<li>Experience with large-scale data pipelines, distributed training systems (e.g., Ray), or experiment management frameworks</li>
<li>Familiarity with camera calibration, geometric reasoning, or 3D perception from images (e.g., BEV, monocular depth, structure-from-motion)</li>
<li>Experience deploying ML models into production or real-world robotics systems </li>
</ul>
Work Location: For this position, we are open to hiring in Montreal, Canada or remote within Canada 
<div>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:</div>
<ul>
<li>A competitive compensation package that includes a bonus component and stock options</li>
<li>Medical, dental, and vision for full-time employees</li>
<li>RRSP plan with a 6% employer match</li>
<li>Public Transit Subsidy (Montreal area only)</li>
<li>Flexibility in schedule and generous paid vacation</li>
<li>Company-wide holiday office closures</li>
<li>Life Insurance</li>
</ul>
 
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: 102952
Salary Range: $168,000-$193,000 CAD

Senior, Machine Learning Engineer - Camera Model

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. <a href="https://torc.ai/daimler-testing-automated-trucks-public/" rel="noopener noreferrer ugc" target="_blank">Now a part of the Daimler family</a>, 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 – Camera Models, you will develop and deploy machine learning models that power camera-based perception for autonomous trucks. The Camera Models team builds and maintains core vision systems that enable the autonomy stack to understand the environment, detect and localize objects, and estimate scene structure from camera data.    Working closely with teams across perception, data, and infrastructure, you will own the development and improvement of robust, scalable camera-based models that support safe and reliable autonomous driving in real-world freight environments.  This role focuses on owning model development for scoped problem areas, improving system performance through iteration, and delivering production-ready machine learning solutions within the autonomy stack.    What You’ll Do 
<ul>
<li>Design, develop, and deploy deep learning models for camera-based perception (e.g., object detection, segmentation, depth estimation, scene understanding)</li>
<li>Own end-to-end model development for scoped areas, from data curation and training to evaluation and deployment</li>
<li>Write production-quality ML code to support scalable training, evaluation, and inference pipelines</li>
<li>Analyze model performance across diverse driving scenarios, identify failure modes, and improve robustness and generalization</li>
<li>Contribute to and improve large-scale training pipelines, including dataset preparation, distributed training, and experiment tracking</li>
<li>Partner with data teams to improve dataset quality, including labeling strategies and coverage of edge cases</li>
<li>Collaborate with perception, simulation, and validation teams to evaluate and integrate models into the autonomy stack</li>
<li>Improve tooling, workflows, and infrastructure to accelerate experimentation and model iteration</li>
<li>Contribute to model architecture decisions and technical discussions within the team</li>
<li>Mentor junior engineers on implementation, debugging, and best practices </li>
</ul>
What You’ll Need to Succeed 
<ul>
<li>Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 6+ years of industry experience, OR Master’s degree with 3+ years OR PhD with 1+ years of experience</li>
<li>Experience developing and deploying deep learning models for computer vision or perception systems</li>
<li>Strong programming skills in Python and PyTorch, with experience writing production-quality ML code</li>
<li>Experience training and evaluating models using large-scale datasets and distributed compute environments</li>
<li>Solid understanding of modern deep learning architectures used in perception (e.g., CNNs, transformers, multi-task models)</li>
<li>Experience debugging model behavior, analyzing performance metrics, and improving model reliability</li>
<li>Ability to translate ambiguous problems into structured ML solutions and deliver independently</li>
<li>Experience collaborating cross-functionally to integrate ML models into larger autonomy or robotics systems </li>
</ul>
Bonus Points: 
<ul>
<li>Experience in autonomous driving, robotics, or simulation-based ML systems</li>
<li>Experience with multi-task learning or unified perception architectures</li>
<li>Experience with large-scale data pipelines, distributed training systems (e.g., Ray), or experiment management frameworks</li>
<li>Familiarity with camera calibration, geometric reasoning, or 3D perception from images (e.g., BEV, monocular depth, structure-from-motion)</li>
<li>Experience deploying ML models into production or real-world robotics systems </li>
</ul>
Work Location: For this position, we are open to hiring in either the Ann Arbor, MI OR Blacksburg, VA (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:
<ul>
<li>A competitive compensation package that includes a bonus component and stock options </li>
<li>100% paid medical, dental, and vision premiums for full-time employees</li>
<li>401K plan with a 6% employer match</li>
<li>Flexibility in schedule and generous paid vacation (available immediately after start date)</li>
<li>Company-wide holiday office closures</li>
<li>AD+D and Life Insurance    </li>
</ul>
 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: 102952<div><div><div>Hiring Range for Job Opening </div><div>US Pay Range</div><div>$177,300—$212,800 USD</div></div></div>

Torc Robotics

Open jobs at Torc Robotics

Senior, ML Engineer - Tracking

Machine Learning Engineer II - Learned Planning (Reinforcement Learning)

Senior, Machine Learning Engineer - Camera Model

Senior, Machine Learning Engineer - Camera Model

Working for Torc Robotics?

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