Jobs at Torc Robotics

• Manage a small team responsible for analysis and metrics reporting, delivering value to Torc internal engineering and Torc customer-facing teams
• Prioritize and assign team workload across triage, metrics, and reporting requests from stakeholders, and remove blockers so the team can deliver

• Define and maintain an account vending machine with appropriate organizational control policies.
• Design and operate shared networks, including Direct Connect, Site-to-Site VPN, and cloud-native network segmentation.

• Lead, coach and develop a team of machine learning and software engineers, including hiring, performance management, career development, and continuous feedback.
• Set the technical direction, roadmap, and priorities for active-sensor perception in alignment with perception and vehicle-level milestones.

JOB DESCRIPTION: Lead efforts to develop high quality product definitions, user journeys, product requirements, and Operational Design Domain (ODD) specifications to deliver next generation on road autonomous driving technology that meets the highest safety standards while supporting the company’...

• Support integration of new and existing self-driving software onto vehicles and test benches.
• Assist with troubleshooting of component and system integration issues, guiding the team to an efficient resolution.

• Design, develop, and deploy production ML models for mulit-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 infrastr...

• Design, implement, and optimize software that creates the interface between Autonomy and the Mission Control, Remote Assistance, Route Advisor, and On Truck Management systems to allow for mission management from planning, initiating, and updating missions to tracking progress and monitoring performance through telemetry

• 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.

• Review HD map geospatial data (lane geometry, road boundaries, intersections, signage, lane connectivity) against internal quality specifications and ground-truth sources
• Perform QC on map features derived from LiDAR point clouds, aerial/satellite imagery, and vehicle-collected sensor data

• 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

• Act as the embedded point of contact between Dataloop + Simulation and one to two Autonomy teams, driving hands-on adoption of Torc Sim
• Implement the end-to-end data flow: data ops platform → simulation environment → persistent storage running at scale

• Lead on-truck bring-up and integration of embedded compute platforms, sensors, networking, and vehicle interfaces, from first power-on through validated, deployable configurations.
• Own integration of platform, embedded, and autonomy software releases onto target hardware, defining acceptance criteria and making the call on integration readiness.

• Design and build scalable, cost-effective mapping and routing data pipelines and services in preparation for commercial launch.
• Take ambiguous or partially-defined problems from internal customers and drive them to a concrete technical design, scoping tradeoffs independently before looping in senior engineers.

• Identify, plan, and execute simulation test campaigns for autonomous vehicle V&V efforts.
• Interface with Product, Systems, and Safety teams to develop V&V simulation strategies.

• Own and evolve the technical architecture for scalable vehicle modeling and simulation — extensible across vehicle types, sensor platforms, and fleet variability as Torc's autonomy program grows.
• Develop and own high-fidelity truck and vehicle dynamics models (longitudinal, lateral, and transient behavior) spanning nominal, off-nominal, and failure-mode simulation domains.

• Lead the architecture, design, implementation, and evolution of core frameworks that serve as the foundation for Torc's autonomous driving stack, including state management, inter-component communication, abstraction layers, and common utilities used across all software systems.
• Drive the technical direction for real-time C++ architectural components and patterns responsib...

• Architect, build, and own backend services and data pipelines that power the map validation and simulation pipelines for the autonomous trucking platform.
• Provide technical leadership to the annotation platform building scalable web-based annotation tooling including cuboid and polygon editing, cross-frame interpolation and track propagation, attribute editing, and review-first (accept/reject) workflows.

• Scenario Mining at Scale: Architect and optimize distributed data pipelines to process massive multi-sensor logs (camera, LiDAR, radar, kinematics), automatically extracting and cataloging safety-critical and long-tail driving events.
• Advanced Event Tagging: Develop and tune both heuristic-based and ML-assisted algorithms (inclu...

• 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.

• Create robust and resilient pipelines to process massive daily volumes of data created by vehicle fleets and simulation environments
• Build and support scalable pipelines as part of Torc’s Data Factory to deliver data for ML training at scale