Senior ML Engineer - Tracking
New
T
TorcAutonomous vehicles
Remote - USFull-TimeSenior
SalaryUS Pay Range $177,300 — $212,800 USD
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Job Details
- Experience
- Bachelor’s degree ... 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.
- Required Skills
- PythonPyTorchC++
Requirements
- Have a Bachelor’s degree in Computer Science, Software Engineering, Robotics, or a related field with 6+ years of relevant industry experience; a Master’s degree with 3+ years; or a PhD with 1+ year.
- Have experience with AV or robotics perception systems, such as tracking, detection, SLAM, or scene modeling.
- Have experience developing and deploying ML models for perception, localization, or sensor fusion.
- Be proficient with PyTorch and modern ML tooling for training, inference, and optimization.
- Understand 3D geometry, probabilistic estimation, coordinate transforms, and robotics fundamentals.
- Be able to work with large multimodal datasets and build scalable pipelines for processing, labeling, and evaluation.
- Have strong software engineering fundamentals in Python and C++, including algorithms, data structures, testing, debugging, and performance optimization.
- Have strong written and verbal communication skills and the ability to work effectively on cross-functional teams.
- Experience with state estimation techniques such as factor graphs, Kalman filtering, or nonlinear optimization is a bonus.
- Familiarity with Ray, Kubernetes, or similar distributed computing and orchestration frameworks is a bonus.
- Knowledge of embedded and real-time constraints for on-vehicle deployment is a bonus.
- Experience in simulation, synthetic data generation, or uncertainty-aware ML modeling is a bonus.
Responsibilities
- Design, develop, and deploy production ML models for multi-object tracking, including association, learned pose and kinematic estimation, and sensor fusion.
- Develop scalable training and evaluation workflows using PyTorch, distributed training infrastructure, and large-scale real-world datasets.
- Design and improve tracking and sensor fusion algorithms for robust vehicle pose and kinematics.
- 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 for Tracking quality, robustness, and safety.
- Make technical design and architecture decisions that balance 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 engineering best practices.
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