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 – 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

• Design, develop, and deploy deep learning models for camera-based perception (e.g., object detection, segmentation, depth estimation, scene understanding)
• Own end-to-end model development for scoped areas, from data curation and training to evaluation and deployment
• Write production-quality ML code to support scalable training, evaluation, and inference pipelines
• Analyze model performance across diverse driving scenarios, identify failure modes, and improve robustness and generalization
• Contribute to and improve large-scale training pipelines, including dataset preparation, distributed training, and experiment tracking
• Partner with data teams to improve dataset quality, including labeling strategies and coverage of edge cases
• Collaborate with perception, simulation, and validation teams to evaluate and integrate models into the autonomy stack
• Improve tooling, workflows, and infrastructure to accelerate experimentation and model iteration
• Contribute to model architecture decisions and technical discussions within the team
• Mentor junior engineers on implementation, debugging, and best practices

What You’ll Need to Succeed

• 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
• Experience developing and deploying deep learning models for computer vision or perception systems
• Strong programming skills in Python and PyTorch, with experience writing production-quality ML code
• Experience training and evaluating models using large-scale datasets and distributed compute environments
• Solid understanding of modern deep learning architectures used in perception (e.g., CNNs, transformers, multi-task models)
• Experience debugging model behavior, analyzing performance metrics, and improving model reliability
• Ability to translate ambiguous problems into structured ML solutions and deliver independently
• Experience collaborating cross-functionally to integrate ML models into larger autonomy or robotics systems

Bonus Points:

• Experience in autonomous driving, robotics, or simulation-based ML systems
• Experience with multi-task learning or unified perception architectures
• Experience with large-scale data pipelines, distributed training systems (e.g., Ray), or experiment management frameworks
• Familiarity with camera calibration, geometric reasoning, or 3D perception from images (e.g., BEV, monocular depth, structure-from-motion)
• Experience deploying ML models into production or real-world robotics systems

Work Location: For this position, we are open to hiring in either the Torc Montreal, Quebec (Canada) or Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States or Canada.

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 6% 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. 

Job ID:  R-102584

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. 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 

The Autonomous Driving Kit Component Enablement & Calibration (ADkit CE&E) team plays a vital role in ensuring the accuracy and reliability of perception systems across our autonomous vehicle platform.  

We are currently seeking a Senior Software Engineer who is enthusiastic about thriving in a hands-on environment and ready to grow with the team and leading our way toward productization. 

We develop, research and design scalable solutions to calibrate and configure the ADKit components to their peak operational possible state. We work with multi-modal sensors systems including cameras, Lidars, radars and IMU on real vehicles and Hardware-in-the-Loop systems to develop our best-in-class sensors spatial orientation. Our contribution directly supports the safety, performance, and robustness of autonomous driving capabilities.  

We design adaptability into our software to support the wide range of ADkit sensor configuration needed to keep our truck generation operation on the path to productization. The team engages with diverse stakeholder, spanning from commercial partners to end customers, to reduce calibration related obstacle associated with adopting autonomous trucking.  

Your role will make a significant impact on the future of trucking and autonomous technology as we look to Drive the Future of Freight.  

What You’ll Do 

As a Senior Software Engineer on AdKit CE&C, you will be directly involved in bringing our software solution toward its long-term implementation. To successfully accomplish this, you would need to:  

• Own the design and architecture for a scalable sensor calibration pipeline in C++, leveraging available libraries (OpenCV, linear algebra libraries) for real-time and offline calibration. 

• Deep expertise in linear algebra to lead the design and implementation of spatial computational system for multi-modals sensor platforms. Apply advanced mathematical rigor using Lie groups, quaternions, and 3D transformations to ensure accurate spatial calibration.  

• Lead the development of specialized dedicated libraries allowing sensor-to-sensor extrinsic calibration (lidar-camera, imu-lidar, etc.) using multi-sensor targetless detections during robotics missions.  

• Experience with camera intrinsic and extrinsic calibration.  

• Drive the design and maintenance of simulation tools and data pipelines for sensor modeling, calibration validation, and large-scale regression testing. 

• Collaborate cross-functionally with perception, simulation, and platform teams to define calibration requirements, set best practices, and ensure robustness across hardware configurations and software releases. 

• Establish and maintain CI/CD-integrated calibration workflows using Docker, Bazel, and Git to enable reproducible, automated testing and deployment. 

• Lead deep-dive debugging and root-cause analysis of complex sensor alignment issues in vehicle logs and simulation using ROS tools, rviz, and custom visualization utilities. 

• Mentor junior engineers and contribute to technical reviews, fostering a culture of high-quality software design and code excellence. 

What You’ll Need to Succeed 

• Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering, or a related field with 5–7+ years of experience (or a Master’s Degree with 3–5+ years of experience). 

• Proven expertise in Python and C++ for algorithm development, system design, and high-performance tooling. 

• Advanced experience with OpenCV, ROS, and numerical libraries for computer vision and robotics applications. 

• Deep understanding of multi-sensor calibration (camera, Lidar, IMU) in robotics or autonomous systems. 

• Strong mathematical foundation in 3D geometry, non-linear optimization, and matrix math, including SE(3) and SO(3) transformations. 

• Proficiency in Linux development, version control (Git), containerization (Docker), and build systems (Bazel). 

• Demonstrated experience designing scalable software architectures and leading technical initiatives. 

• Excellent problem-solving skills and ability to drive cross-team technical alignment. 

Bonus Points! 

• Familiarity with non-linear least squares solvers (e.g., Ceres, g2o) and large-scale optimization. 

• Background in sensor simulation, synthetic data generation, or validation frameworks. 

• Prior contributions to ROS-based open-source calibration or robotics tools. 

• Experience influencing technical roadmaps and defining long-term software strategies. 

• Uses vim as a primary editor (yes, still really). 

• Willingness to travel occasionally. 

Knowledge of English is required since the selected candidate will need to collaborate daily with English-speaking colleagues in the United States and work with technical documentation written exclusively in English. 

Work Location: For this position, we are open to hiring in either the Torc Montreal, Quebec (Canada) or Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States or Canada.

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 6% 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. 

Job ID: 102610

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. 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 

The Autonomous Driving Kit Component Enablement & Calibration (ADkit CE&E) team plays a vital role in ensuring the accuracy and reliability of perception systems across our autonomous vehicle platform.  

We are currently seeking a Senior Software Engineer who is enthusiastic about thriving in a hands-on environment and ready to grow with the team and leading our way toward productization. 

We develop, research and design scalable solutions to calibrate and configure the ADKit components to their peak operational possible state. We work with multi-modal sensors systems including cameras, Lidars, radars and IMU on real vehicles and Hardware-in-the-Loop systems to develop our best-in-class sensors spatial orientation. Our contribution directly supports the safety, performance, and robustness of autonomous driving capabilities.  

We design adaptability into our software to support the wide range of ADkit sensor configuration needed to keep our truck generation operation on the path to productization. The team engages with diverse stakeholder, spanning from commercial partners to end customers, to reduce calibration related obstacle associated with adopting autonomous trucking.  

Your role will make a significant impact on the future of trucking and autonomous technology as we look to Drive the Future of Freight.  

What You’ll Do 

As a Senior Software Engineer on AdKit CE&C, you will be directly involved in bringing our software solution toward its long-term implementation. To successfully accomplish this, you would need to:  

• Own the design and architecture for a scalable sensor calibration pipeline in C++, leveraging available libraries (OpenCV, linear algebra libraries) for real-time and offline calibration. 

• Deep expertise in linear algebra to lead the design and implementation of spatial computational system for multi-modals sensor platforms. Apply advanced mathematical rigor using Lie groups, quaternions, and 3D transformations to ensure accurate spatial calibration.  

• Lead the development of specialized dedicated libraries allowing sensor-to-sensor extrinsic calibration (lidar-camera, imu-lidar, etc.) using multi-sensor targetless detections during robotics missions.  

• Experience with camera intrinsic and extrinsic calibration.  

• Drive the design and maintenance of simulation tools and data pipelines for sensor modeling, calibration validation, and large-scale regression testing. 

• Collaborate cross-functionally with perception, simulation, and platform teams to define calibration requirements, set best practices, and ensure robustness across hardware configurations and software releases. 

• Establish and maintain CI/CD-integrated calibration workflows using Docker, Bazel, and Git to enable reproducible, automated testing and deployment. 

• Lead deep-dive debugging and root-cause analysis of complex sensor alignment issues in vehicle logs and simulation using ROS tools, rviz, and custom visualization utilities. 

• Mentor junior engineers and contribute to technical reviews, fostering a culture of high-quality software design and code excellence. 

What You’ll Need to Succeed 

• Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering, or a related field with 5–7+ years of experience (or a Master’s Degree with 3–5+ years of experience). 

• Proven expertise in Python and C++ for algorithm development, system design, and high-performance tooling. 

• Advanced experience with OpenCV, ROS, and numerical libraries for computer vision and robotics applications. 

• Deep understanding of multi-sensor calibration (camera, Lidar, IMU) in robotics or autonomous systems. 

• Strong mathematical foundation in 3D geometry, non-linear optimization, and matrix math, including SE(3) and SO(3) transformations. 

• Proficiency in Linux development, version control (Git), containerization (Docker), and build systems (Bazel). 

• Demonstrated experience designing scalable software architectures and leading technical initiatives. 

• Excellent problem-solving skills and ability to drive cross-team technical alignment. 

Bonus Points! 

• Familiarity with non-linear least squares solvers (e.g., Ceres, g2o) and large-scale optimization. 

• Background in sensor simulation, synthetic data generation, or validation frameworks. 

• Prior contributions to ROS-based open-source calibration or robotics tools. 

• Experience influencing technical roadmaps and defining long-term software strategies. 

• Uses vim as a primary editor (yes, still really). 

• Willingness to travel occasionally. 

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. 

U.S Compensation Range: $160,000-193,000/yr

Job ID: 102610

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 

• Develop and train machine learning models for learned behavior systems, including approaches such as behavior cloning, imitation learning, and reinforcement learning. 

• Implement production-quality ML code to support model training, evaluation, and inference within the autonomy stack. 

• Analyze model performance, identify failure modes, and propose improvements to increase robustness and generalization across scenarios. 

• Contribute to model training pipelines and data workflows, curating behavior datasets from simulation, fleet logs, and on-vehicle data. 

• Collaborate with simulation, validation, and autonomy engineering teams to test and evaluate learned behavior models across diverse driving environments. 

• Help integrate learned behavior models into simulation and testing workflows, enabling faster iteration and more comprehensive validation. 

• Support the development of tooling and infrastructure that improves experimentation speed, reproducibility, and model iteration. 

• Contribute to technical discussions around model architecture and training strategies within the team. 

 
 
 
 
What You’ll Need to Succeed 

• 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. 

• Experience applying machine learning techniques such as imitation learning, reinforcement learning, or sequence modeling to robotics, autonomous systems, or complex control environments. 

• Strong programming skills in Python and PyTorch, with experience writing production-quality ML code. 

• Experience training and evaluating machine learning models using large datasets and scalable compute environments. 

• Understanding of ML architectures used in autonomy systems, such as transformers, graph neural networks, or sequence models. 

• Experience debugging model behavior, analyzing performance metrics, and iterating on training pipelines. 

• Ability to collaborate with cross-functional teams to integrate ML models into larger software systems. 

 
 
Bonus Points! 

• Experience working in autonomous driving, robotics, or simulation-based training environments. 

• Experience with reinforcement learning frameworks or distributed training systems (e.g., Ray). 

• Experience working with simulation environments or large-scale behavior datasets. 

• Familiarity with vehicle dynamics, motion planning, or multi-agent decision-making systems. 

• Experience deploying ML models into production or real-world robotics systems. 

Hiring Range for Job Opening  

US Pay Range 

$153,200 - $183,300 USD 

Job ID: 102515

Meet the Team: 
As a Machine Learning Engineer II – Scene Model, you will help develop and deploy machine learning models that enable autonomous trucks to understand their surrounding environment. Our team focuses on building multi-modal perception systems in bird’s-eye-view (BEV) that fuse information from LiDAR, cameras, radar, and map inputs to produce a unified representation of the scene.  

Working closely with teams across perception, prediction, planning, and platform infrastructure, you will contribute to models that detect objects, understand road structure, and generate spatial temporal representations used by downstream autonomy systems.  

This role focuses on developing and improving deep learning models, training pipelines, and data workflows that power scene understanding within the autonomy stack. 

What You’ll Do 

• Develop and train machine learning models for scene understanding, including tasks such as object detection, road and lane prediction, semantic voxel grid classification, occupancy prediction, and map understanding in bird’s-eye-view (BEV) space. 

• Implement production-quality ML code to support model training, evaluation, and inference within the perception stack. 

• Analyze model performance, identify failure modes, and propose improvements to increase robustness across diverse driving environments and conditions. 

• Identify and interpret objects, lanes, obstacles, and weather conditions in the driving environment. 

• Apply data science techniques to analyze model performance, understand data distributions, and identify corner cases. 

• Contribute to multi-modal perception systems, combining signals from LiDAR, cameras, radar, and map sources into unified scene representations. 

• Work with large-scale datasets from simulation, fleet logs, and on-vehicle data to curate training data and improve model performance. 

• Collaborate with data, deployment, and infrastructure teams to evaluate perception models and ensure reliable performance in real-world driving scenarios. 

• Help integrate perception models into the autonomy stack and testing pipelines, enabling faster experimentation and iteration. 

• Contribute to tooling and infrastructure that improves training efficiency, experiment tracking, and reproducibility. 

• Participate in technical discussions around model architectures, sensor fusion strategies, and training approaches within the team.  

What You’ll Need to Succeed 

• 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. 

• Strong understanding of computer-vision, and machine learning basics. 

• Experience applying machine learning techniques such as imitation learning, reinforcement learning, or sequence modeling to robotics, autonomous systems, or complex control environments. 

• Strong programming skills in Python and PyTorch, with experience writing production-quality ML code. 

• Experience training and evaluating machine learning models using large datasets and scalable compute environments. 

• Understanding of ML architectures used in autonomy systems, such as transformers, graph neural networks, or sequence models. 

• Experience debugging model behavior, analyzing performance metrics, and iterating on training pipelines. 

• Ability to collaborate with cross-functional teams to integrate ML models into larger software systems. 

• Good technical communication skills, written and verbal. 

• A positive team-player mindset.  

Bonus Points! 

• PhD in machine learning or data science. 

• Experience working in autonomous driving, robotics, or simulation-based training environments. 

• Experience with distributed training frameworks or large-scale ML infrastructure (e.g., Ray, Anyscale). 

• Experience working with simulation environments or large-scale behavior datasets. 

• Familiarity with vehicle dynamics, motion planning, or multi-agent decision-making systems. 

• Experience deploying ML models into production or real-world robotics systems. 

• Experience with multi-modal sensor fusion, including LiDAR, cameras, radar, or map inputs. 

• Experience working with BEV representations, occupancy grids, or 3D scene representations. 

Hiring Range for Job Opening  

US Pay Range 

$153,200 - $183,300 USD 

Job ID: 102517

Meet the Team: 
As a Machine Learning Engineer II – End-to-End, you will help develop and deploy End-to-End models that power both perception and decision-making for autonomous trucks. Working closely with teams across perception, prediction, planning, and safety, you will contribute to End-to-End models 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 End-to-End systems within the autonomy stack. 
 
What You’ll Do 

• Develop and train machine learning models for End-to-End percetion and planning, including approaches such as imitation learning and reinforcement learning. 

• Implement production-quality ML code to support model training, evaluation, and inference within the autonomy stack. 

• Analyze model performance, identify failure modes, and propose improvements to increase robustness and generalization across scenarios. 

• Contribute to model training pipelines and data workflows, curating datasets from simulation, fleet logs, and on-vehicle data. 

• Collaborate with simulation, validation, and autonomy engineering teams to test and evaluate End-to-End models across diverse driving environments. 

• Help integrate End-to-End models into simulation and testing workflows, enabling faster iteration and more comprehensive validation. 

• Support the development of tooling and infrastructure that improve experimentation speed, reproducibility, and model iteration. 

• Contribute to technical discussions around model architecture and training strategies within the team. 

 
 
 
 
What You’ll Need to Succeed 

• 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. 

• Experience applying machine learning techniques such as computer vision, imitation learning, or reinforcement learning, to robotics, autonomous systems, or complex control environments. 

• Strong programming skills in Python and PyTorch, with experience writing production-quality ML code. 

• Experience training and evaluating machine learning models using large datasets and scalable compute environments. 

• Understanding of ML architectures used in End-to-End systems, such as BEV models, Transformers, VLA, or diffusion models. 

• Experience debugging model behavior, analyzing performance metrics, and iterating on training pipelines. 

• Ability to collaborate with cross-functional teams to integrate ML models into larger software systems. 

 
 
Bonus Points! 

• Experience working in autonomous driving, robotics, or simulation-based training environments. 

• Experience with reinforcement learning frameworks or distributed training systems (e.g., Ray). 

• Experience with VLA or Neural Rendering. 

• Familiarity with vehicle dynamics, motion planning, or multi-agent decision-making systems. 

• Experience deploying ML models into production or real-world robotics systems. 

Hiring Range for Job Opening  

US Pay Range 

$153,200 - $183,300 USD 

Job ID: 102514

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 specializing in BEV (Bird’s-Eye View) and Multi-Modal Perception, you will lead the development of next-generation models that unify information across cameras, LiDAR and radar to deliver a rich spatial understanding of the driving environment. 

You will drive architectural innovation, large-scale model training, and data-driven improvements that directly advance the perception capabilities at the heart of Torc’s autonomous driving stack. 

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

What You’ll Do 

• Lead BEV model development: Define and execute the technical roadmap for BEV-based perception models across multiple tasks (e.g., detection, segmentation, road topology, and scene understanding). 
• Design advanced multi-modal architectures that fuse heterogeneous sensor data (camera, LiDAR, radar, HD maps) into unified spatial representations.
• Develop foundational perception models leveraging BEV transformers, voxel-based encoders, or implicit scene representations.
• Own large-scale training workflows — from data sampling strategies and augmentation pipelines to distributed training and hyperparameter optimization.
• Advance model robustness and generalization, addressing long-tail conditions such as low visibility, occlusions, and rare scene configurations.
• Establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer performance.
• Collaborate cross-functionally with sensor calibration, mapping, and fusion teams to ensure cohesive perception model interfaces.
• Mentor and guide ML engineers, cultivating best practices in experimentation, code quality, and model validation.
• Stay at the forefront of ML research, exploring self-supervised learning, large-scale pretraining, or foundation models for 3D perception. 

What You’ll Need to Succeed 

• 10+ years of experience in deep learning for perception, 3D vision, and/or autonomous systems
• M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, or related field (or equivalent practical experience).
• Proven expertise in BEV modeling, 3D scene understanding, and multi-view fusion.
• Strong background in multi-modal sensor fusion, particularly integrating camera and LiDAR data.
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Experience with large-scale data pipelines, distributed training, and experiment management systems.
• Demonstrated leadership in driving ML model innovation and mentoring technical teams. 

Bonus Points! 

• Experience with autonomous driving or robotics perception in production environments.
• Experience with MLOps and infrastructure tools (Ray)
• Hands-on expertise in BEV-based ML architectures, LiDAR-vision fusion, or spatial-temporal modeling.
• Familiarity with 3D labeling, calibration, and sensor simulation pipelines.
• Track record of publications or open-source contributions in top-tier venues (CVPR, ICCV, NeurIPS, ICRA, CoRL).
• Understanding of performance tradeoffs and deployment constraints (latency, memory, accuracy). 

Knowledge of English is required since the selected candidate will need to collaborate daily with English-speaking colleagues in the United States and work with technical documentation written exclusively in English. 

Work Location: For this position, we are open to hiring in either the Torc Montreal, Quebec (Canada) or Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States or Canada.

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. 

CAD Compensation Range: $209,300-313,800 CAD

Job ID: 102405

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. 

Work Location: For this position, we are open to hiring in either the Torc Montreal, Quebec (Canada) or Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States or Canada.

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 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:  

Pseudo-Labeling team's goal is to create high quality annotations on sensor data (images, point clouds). The annotations include 2D, 3D bounding boxes, classes, trajectories, lane lines, segmentations, depths etc. The annotations are then used by different downstream users, for example, perception teams use it to train various models and simulation teams use it for generating new data. 

What You’ll Do:  

• Design, implement, test and deploy offline object detection, tracking and fusion modules to automatically create annotations on Cloud Services from logged sensor data (Cameras, Lidars, Radars)
• Demonstrated project management skills, serving as project lead guiding less experienced team members in multiple facets of project execution. 
• Stay up to date with the latest developments in AI and ML for autonomous driving.
• Independently develop offline perception models or algorithms using disciplined software development processes, making recommendations for developing new code or re-using existing code, implementing version control, and maintaining 
• Documentation of created applications. 
• Define and implement ingestion, data preparation, curation, and governance of large, multi-faceted data sets supporting analytics models and workflows. 
• Proactively assess current capabilities to identify areas for improvement proposing solutions that align with core strategy and operation. 
• Measure and track auto labeling quality to meet internal customer requirements.
• Guide and produce information products, supporting visualization and data accessibility in a customer-centric manner. 
• Evaluate and make recommendations regarding technical advances that improve productivity and quality, reduce flow times, and enhance operational surety. 
• Develop guidelines and standards for analytics and machine learning models, their deployment, and associated processes.  
• Provides technical guidance or business process expertise, technical leadership, coaching and mentoring to team members.  

What You’ll Need to Succeed:  

• Considered highly skilled and proficient in discipline; conducts complex, important work under minimal supervision and with wide latitude for independent judgment. 
• Scope of Influence: Expected to drive alignment across team interfaces to the rest of the organization. Designs, maintains and owns team technical solutions and drives consensus.  Mentors and guides engineers within the group.  
• Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 6+ years of experience OR;  
• Master’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 3+ years of experience OR; 
• Doctorate Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 1+ years of experience. 
• Required Qualifications (some combination of the following skills):    
  • Active Learning & Pseudo-labeling - Computer Vision, Deep Learning, Model training.
  • Two of the following: 2D/3D Object Detection, Tracking, Sensor Fusion, Semantic Segmentation, SLAM, BEV.
  • Scaled ML Operations (MLOps) and Tooling – ML Frameworks, experiment tracking, model registry, MLFLow, Weights and Biases, ML Metrics and Evaluation / Quality. 
  • Distributed machine learning frameworks - PyTorch, Lightning, Ray. 
  • Model Data Curation - Parquet data processing (PyArrow, Daft, Pandas, etc). 
  • Development Tools & Eco-System (at scale) - Proficiency in Python software development. Also, VDI and cloud-based development environments, CI Systems (GitHub Actions), and Docker.  

Bonus Points! 

• Data operations and management at scale - Schema design, AWS storage and processing infra, vector databases / LanceDB, file formats (MCAP, parquet, etc). 
• Data Visualization - Integration with tooling such as OpenGL, 3.js, foxglove, 51, tableau. 
• Cloud Development – Python (proficient level), Terraform, AWS Managed Services (eg S3, ECS, Lambda, Dynamo, Step Functions, Athena).   
• Cloud-based orchestration and resource management - AWS Hyperpods, Anyscale, Etc. Model Inference Orchestration.  

Knowledge of English is required since the selected candidate will need to collaborate daily with English-speaking colleagues in the United States and work with technical documentation written exclusively in English. 

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 

Canada Pay Range 

$199,200 to $298,800 CAD 

Job ID: 102399

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:    

Torc is marching towards its AV 3.0 strategy. Simulation and Data Generation are key elements towards autonomous trucking. The team builds the sensor simulation based on Neural Rendering and Generative models for Torc’s data-driven simulator. High-quality data from novel scenarios close the domain data gap, solving one of the biggest challenges for safe autonomous driving.  The team works on state-of-the-art approaches for Neural Rendering and data generation for camera, LiDAR, and Radar sensor data, that contributes to the Torc’s data workflow for training and validation across the complete AV stack.   

What You’ll Do:    

• Implement the latest research advances in Neural Rendering and generative models 
• Translate cutting edge solution in the domain of autonomous driving for high-quality Camera, LiDAR and Radar sensor simulations 
• Support implementing a neural rendering framework that allows to scale perception simulation and AV 3.0 training 
• Integrate the framework in a cloud environment and automate the pipeline to allow scaling for the target verification and validation of our autonomous trucks  
• Own development projects in the team – From research, design, to implementation, testing and deployment 
• Design, implement, test and deploy shippable production quality software starting from early prototypes using disciplined software development processes.
• Work in the cloud machine learning ecosystem alongside other machine learning services existing in the company.
• Proactively assess current capabilities to identify areas for improvement proposing solutions that align with core strategy and operation. 
• Demonstrate project management skills, serving as project lead guiding less experienced team members in multiple facets of project execution, coaching and mentoring as needed.   

What You’ll Need to Succeed:    

• Proficiency in Python and deep learning frameworks such as PyTorch. 
• PhD or equivalent work experience of 6+ years in relevant fields (CS, Robotics, Electrical Engineering) with industry experience in shipping production software. 
• Proven expertise in Neural Rendering (Neural Radiance Fields and 3D Gaussian Splatting) and generative models (Diffusion Models, Flow Matching). 
• Background in Computer Graphics, 3D Reconstruction, or 3D Computer Vision. 
• Considered highly skilled and proficient in discipline; conducts complex, important work under minimal supervision and with wide latitude for independent judgment.   
• Experience with VDI and cloud based machine learning development environments.
• Expected to drive alignment across team interfaces to the rest of the organization.  
• Designs, maintains and owns team technical solutions and drives consensus.   
• Mentors and guides engineers within the group.    

Bonus Points!  

• Experience with autonomous driving or robotics perception in production environments. 
• Proficiency with CUDA programming for efficient rendering of large-scale scenes 
• Publications in top-tier CV/AI/Graphics conferences (CVPR/ECCV/ICCV, NeurIPS/ICLR/ICML, SIGGRAPH) or journals 
• Experience with MLOps and infrastructure tools (Ray) 
• Familiarity with 3D labeling, calibration, and sensor simulation pipelines.  
• Handling of Autonomous Driving Sensors – Multiple timestamp, multiple sensor data from cameras, lidars, and radars  

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) 
• 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 Base Pay Range:

$160,800 - $212,300

Job ID: R-102432

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:    

Torc is marching towards its AV 3.0 strategy. Simulation and Data Generation are key elements towards autonomous trucking. The team builds the sensor simulation based on Neural Rendering and Generative models for Torc’s data-driven simulator. High-quality data from novel scenarios close the domain data gap, solving one of the biggest challenges for safe autonomous driving.  The team works on state-of-the-art approaches for Neural Rendering and data generation for camera, LiDAR, and Radar sensor data, that contributes to the Torc’s data workflow for training and validation across the complete AV stack.   

What You’ll Do:    

• Implement the latest research advances in Neural Rendering and generative models 
• Translate cutting edge solution in the domain of autonomous driving for high-quality Camera, LiDAR and Radar sensor simulations 
• Support implementing a neural rendering framework that allows to scale perception simulation and AV 3.0 training 
• Integrate the framework in a cloud environment and automate the pipeline to allow scaling for the target verification and validation of our autonomous trucks  
• Own development projects in the team – From research, design, to implementation, testing and deployment 
• Design, implement, test and deploy shippable production quality software starting from early prototypes using disciplined software development processes.
• Work in the cloud machine learning ecosystem alongside other machine learning services existing in the company.
• Proactively assess current capabilities to identify areas for improvement proposing solutions that align with core strategy and operation. 
• Demonstrate project management skills, serving as project lead guiding less experienced team members in multiple facets of project execution, coaching and mentoring as needed.   

What You’ll Need to Succeed:    

• Proficiency in Python and deep learning frameworks such as PyTorch. 
• PhD or equivalent work experience of 6+ years in relevant fields (CS, Robotics, Electrical Engineering) with industry experience in shipping production software. 
• Proven expertise in Neural Rendering (Neural Radiance Fields and 3D Gaussian Splatting) and generative models (Diffusion Models, Flow Matching). 
• Background in Computer Graphics, 3D Reconstruction, or 3D Computer Vision. 
• Considered highly skilled and proficient in discipline; conducts complex, important work under minimal supervision and with wide latitude for independent judgment.   
• Experience with VDI and cloud based machine learning development environments.
• Expected to drive alignment across team interfaces to the rest of the organization.  
• Designs, maintains and owns team technical solutions and drives consensus.   
• Mentors and guides engineers within the group.    

Bonus Points!  

• Experience with autonomous driving or robotics perception in production environments. 
• Proficiency with CUDA programming for efficient rendering of large-scale scenes 
• Publications in top-tier CV/AI/Graphics conferences (CVPR/ECCV/ICCV, NeurIPS/ICLR/ICML, SIGGRAPH) or journals 
• Experience with MLOps and infrastructure tools (Ray) 
• Familiarity with 3D labeling, calibration, and sensor simulation pipelines.  
• Handling of Autonomous Driving Sensors – Multiple timestamp, multiple sensor data from cameras, lidars, and radars  

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) 
• 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 Base Pay Range:

$177,300 - $234,000

Job ID: R-102432