Job description

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 Accurate and highly available information about vehicle motion and position is fundamental to the safe operation of autonomous trucks. Core capabilities such as perception, prediction, planning, and control depend on reliable ego-motion and localization estimates to ensure safe and efficient vehicle behavior. The Ego-Motion & Localization Team develops the ML models, state estimation algorithms, and production software responsible for estimating vehicle pose, velocity, and acceleration 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 localization and sensor fusion solutions and help solve the challenges of bringing autonomous vehicle technology to real-world commercial applications. What You'll Do Design, develop, and deploy production ML models for ego-motion estimation and localization, including learned pose estimation, sensor extrinsic calibration, map matching, and sensor fusion using camera, LiDAR, radar, and other vehicle sensors. Develop scalable training and evaluation workflows using PyTorch, distributed training infrastructure, and large-scale real-world datasets. Design and improve state estimation and sensor fusion algorithms for robust vehicle pose, velocity, and acceleration estimation. Analyze large-scale vehicle data to characterize performance, identify failure modes, and drive model and system improvements. Develop robust, efficient production software in modern C++ and Python across the full development lifecycle. Define evaluation, verification, and validation strategies to ensure localization quality, robustness, and safety across diverse operating conditions. Make technical design and architecture decisions, balancing model performance, computational efficiency, robustness, and production constraints. Collaborate with perception, mapping, planning, controls, and platform teams to deliver integrated autonomous driving capabilities. Provide technical leadership through design reviews, code reviews, mentoring, and development of engineering best practices. What You'll Need to Succeed 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. Experience with AV or robotics localization systems (e.g., LiDAR-based localization, visual odometry, SLAM, or map-based pose estimation). Strong experience developing and deploying ML models for perception, localization, or sensor fusion domains. Proficiency with PyTorch and modern ML tooling for training, inference, and optimization. Solid understanding of 3D geometry, probabilistic estimation, coordinate transforms, and robotics fundamentals. Demonstrated ability to work with large multimodal datasets and build scalable pipelines for processing, labeling, and evaluation. Strong software engineering fundamentals in Python and C++, including algorithms, data structures, testing, debugging, and performance optimization. Strong written and verbal communication skills and the ability to work effectively on cross-functional teams. Bonus Points Experience with state estimation techniques such as factor graphs, Kalman filtering, nonlinear optimization, or related probabilistic estimation methods. Familiarity with distributed computing tools such as Ray, Kubernetes, or similar orchestration frameworks. Knowledge of embedded and real-time constraints for on-vehicle deployment. Experience in simulation, synthetic data generation, and uncertainty-aware ML modeling. Contributions to open-source robotics, perception, or ML frameworks. Familiarity with functional safety standards and automotive development processes, including ISO 26262. Work Location: For this position, we are open to hiring in Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States. Perks of Being a Full-time Torc’r Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers: A competitive compensation package that includes a bonus component and stock options 100% paid medical, dental, and vision premiums for full-time employees 401K plan with a 6% employer matchFlexibility in schedule and generous paid vacation (available immediately after start date)Company-wide holiday office closures AD+D and Life Insurance At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities. Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply. Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. Job ID: 102894 Hiring Range for Job Opening US Pay Range $177,300 — $212,800 USD

Requirements

Must-haves

Develop scalable training and evaluation workflows using PyTorch, distributed training infrastructure, and large-scale real-world datasets.
Design and improve state estimation and sensor fusion algorithms for robust vehicle pose, velocity, and acceleration estimation.
Analyze large-scale vehicle data to characterize performance, identify failure modes, and drive model and system improvements.
Develop robust, efficient production software in modern C++ and Python across the full development lifecycle.
Define evaluation, verification, and validation strategies to ensure localization quality, robustness, and safety across diverse operating conditions.
Make technical design and architecture decisions, balancing model performance, computational efficiency, robustness, and production constraints.
Collaborate with perception, mapping, planning, controls, and platform teams to deliver integrated autonomous driving capabilities.
Provide technical leadership through design reviews, code reviews, mentoring, and development of engineering best practices.
What You'll Need to Succeed
Experience with AV or robotics localization systems (e.g., LiDAR-based localization, visual odometry, SLAM, or map-based pose estimation).
Strong experience developing and deploying ML models for perception, localization, or sensor fusion domains.
Proficiency with PyTorch and modern ML tooling for training, inference, and optimization.
Solid understanding of 3D geometry, probabilistic estimation, coordinate transforms, and robotics fundamentals.

Nice-to-haves

Experience with state estimation techniques such as factor graphs, Kalman filtering, nonlinear optimization, or related probabilistic estimation methods.
Familiarity with distributed computing tools such as Ray, Kubernetes, or similar orchestration frameworks.
Knowledge of embedded and real-time constraints for on-vehicle deployment.
Experience in simulation, synthetic data generation, and uncertainty-aware ML modeling.
Contributions to open-source robotics, perception, or ML frameworks.
Familiarity with functional safety standards and automotive development processes, including ISO 26262.
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:
100% paid medical, dental, and vision premiums for full-time employees
Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlpythonkubernetes

Platform: greenhouse
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Benefits

Benefits detected in the listing.

Dental

Vision

401k