Senior ML Engineer – Tracking

Torc Robotics

. 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 .

Posted 10/6/2026full-timeRemote • United StatesSenior💰 $177,300 - $212,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying machine learning models for multi-object tracking and sensor fusion, with strong proficiency in Python and C++. Capable of analyzing large-scale vehicle data and collaborating effectively across cross-functional teams to enhance autonomous driving capabilities.

Highest-signal resume keywords

Machine Learning Model DevelopmentSensor Fusion AlgorithmsProficiency in PyTorchC++ and Python Software EngineeringAV or Robotics Perception Systems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningMulti-Object TrackingSensor Fusion3D GeometryProbabilistic EstimationData StructuresAlgorithmsTestingDebuggingPerformance Optimization

Soft Skills

Strong Communication SkillsCross-Functional Collaboration

Tools & Technologies

PyTorchRayKubernetesDistributed ComputingSimulation Tools

Industry Keywords

Autonomous VehiclesRoboticsSLAMISO 26262Functional Safety Standards

Tech Stack

Tools & technologies

KubernetesPythonPyTorchRayC++

About the role

Key responsibilities & impact

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
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 to ensure tracking 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

Requirements

What you’ll need

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 perception systems (tracking, detection, SLAM, scen modeling, ect.)
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: Experience with state estimation techniques such as factor graphs, Kalman filtering, nonlinear optimization, or related probabilistic estimation methods
Bonus: Familiarity with distributed computing tools such as Ray, Kubernetes, or similar orchestration frameworks
Bonus: Knowledge of embedded and real-time constraints for on-vehicle deployment
Bonus: Experience in simulation, synthetic data generation, and uncertainty-aware ML modeling
Bonus: Contributions to open-source robotics, perception, or ML frameworks
Bonus: Familiarity with functional safety standards and automotive development processes, including ISO 26262

Benefits

Comp & perks

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
Potential sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package