Jobs at Torc Robotics

Lead the release lifecycle for self-driving software, coordinating engineering, product, fleet, V&V, and safety stakeholders. Manage release trains, Git branching and tagging, impact analysis, release artifacts, configuration baselines, audits, approvals, documentation, and release meetings. Improve release processes, mentor team members, and support production systems from prototype through launch and field maintenance in complex, safety-critical environments.

Lead functional safety and SOTIF activities for autonomous trucking systems. Responsibilities include hazard analysis and risk assessment, FTTI evaluation, inductive and deductive safety analyses, safety case development, safety performance tracking, artifact reviews, and alignment of safety processes with systems engineering teams. The role requires expertise in ISO 26262, ISO 21448, HAZOP, FMEA, STPA, FTA, and safety-critical autonomous technologies, with occasional travel of 10% or less.

Supports engineering quality assurance across autonomous driving systems and software development. Reviews work products, requirements, verification evidence, traceability, baselines, and release artifacts for completeness and compliance. Performs assessments against QMS and safety standards, documents risks and nonconformities, supports audits and corrective actions, monitors quality metrics, and guides cross-functional engineering teams on process adherence and continuous improvement.

Develops safety behavior requirements for autonomous vehicle systems, leads risk evaluations and functional insufficiency analyses, defines acceptance criteria, and supports safety-critical initiatives throughout the autonomous vehicle lifecycle. The role ensures traceability across hazards, requirements, verification, and validation evidence; contributes to safety cases and assessments; and coordinates cross-functional safety activities involving software, hardware, perception, localization, controls, systems engineering, and field operations.

Lead the architecture, implementation, and evolution of core C++ frameworks supporting an autonomous driving stack. Drive system-wide data flow, component coordination, testing, observability, reliability, and performance improvements. Collaborate with Behavior and Perception teams, conduct architecture and code reviews, mentor engineers, define simulation and validation frameworks, resolve complex platform issues, and establish scalable software engineering standards.

Designs, develops, tests, secures, and supports enterprise application integrations and data flows across HCM, ERP, CRM, and IAM systems. Maintains APIs, automation tooling, code repositories, policies, documentation, and integration standards. Provides application support, evaluates new systems, collaborates with vendors and technical teams, and participates in migrations, upgrades, implementations, and change management. Requires a computer-related bachelor’s degree or equivalent experience, SDLC knowledge, and familiarity with database architecture and ETL tools.

Provides technical leadership for compute platform integration across hardware, software, networking, sensors, safety, and validation. Owns system architecture, electrical/software interfaces, integration milestones, release readiness, risk resolution, requirements traceability, and verification strategies. Collaborates with engineering, OEM, validation, diagnostics, and safety teams to deliver production-ready autonomous vehicle compute platforms. Mentors senior engineers and guides technical roadmaps, design reviews, debugging, and platform scalability.

Leads safety-critical program execution for autonomous vehicle capabilities from concept through deployment. Establishes requirements traceability, coordinates hazard analysis and safety assessments, drives verification and validation planning, manages cross-functional risks and dependencies, monitors safety and program metrics, and facilitates governance reviews. The role requires deep knowledge of ISO 26262 and related safety standards, experience with autonomous or other safety-critical systems, and a technical degree with 1–6+ years of experience depending on education level.

Lead systems engineering for autonomous driving kit compute platforms, including requirements decomposition, traceability, functional architecture, integration and test planning, and lifecycle validation. Collaborate across product, hardware, software, and safety teams while supporting embedded compute, sensors, data logging, and power distribution. Drive root-cause analysis and problem resolution during design, prototyping, and production. Apply automotive ECU methodologies, functional safety, cybersecurity, and requirements management practices.

Leads a team responsible for hardware-in-the-loop verification and validation of autonomous trucks. Owns HiL strategy, roadmap, test campaigns, bench development, requirements traceability, safety compliance, defect triage, and V&V reporting. Partners with product, systems, safety, tools, and external vendor teams. Guides testing aligned with ISO 26262 and ISO 21448, including fault handling, safety mechanisms, autonomous driving systems, and performance limitations.

Annoter et réviser des données provenant d’images 2D et de capteurs 3D, notamment LiDAR, afin d’entraîner les systèmes d’intelligence artificielle de véhicules autonomes. La personne retenue créera des boîtes englobantes et des cuboïdes 3D, corrigera les annotations pré-étiquetées, suivra des lignes directrices détaillées, documentera les corrections et collaborera avec une équipe anglophone.

Lead product strategy for next-generation autonomous driving technology, including product definitions, user journeys, requirements, ODD specifications, roadmaps, metrics, and safety standards. Collaborate with engineering, regulatory, marketing, commercialization, fleet, and customer teams. Prioritize features, assess competitive products, manage technical and execution risks, track milestones, and mentor junior employees.

Leads a team responsible for simulation-based verification and validation of autonomous trucks. Defines V&V strategy, scenario coverage, test campaigns, toolchain requirements, and safety-case evidence aligned with automotive standards. Partners with product, systems, safety, engineering, tools teams, and vendors to establish release criteria, identify testing gaps, analyze results, and report risks and progress to leadership. The role also involves team development, simulation scenario management, and advancing autonomous vehicle validation practices.

Leads vehicle-level verification and validation for L4 autonomous trucks. Defines test strategies, develops scenario-based test coverage, analyzes ground-truth and onboard vehicle data, and manages test platforms and toolchains. Builds and mentors test engineering teams, oversees budgets and schedules, prioritizes safety risks, and communicates results to leadership. The role also supports safety cases, regulatory and customer audits, software tool qualification, and compliance with automotive safety standards.

Leads technical excellence and integration for metrics, release, and Hardware-in-the-Loop systems supporting autonomous driving software. Architects scalable validation platforms, distributed compute and telemetry pipelines, requirements traceability, automated testing, KPI reporting, and subsystem integration. Serves as a systems engineering subject matter expert, drives standards adoption, troubleshoots robotic and automotive systems, and mentors engineers across teams.

Lead and grow a machine learning and software engineering team building production LiDAR and radar perception systems for autonomous trucks. Own technical direction, roadmap, model development, evaluation, integration, deployment, and monitoring. Guide multitask perception, sensor fusion, robustness, and graceful degradation across adverse conditions. Collaborate cross-functionally, manage dependencies and milestones, maintain engineering standards, and communicate risks and progress to leadership.

Develop and deploy machine learning models and production software for multi-object tracking in autonomous trucks. Responsibilities include sensor fusion across camera, LiDAR, and radar; scalable PyTorch training workflows; tracking algorithm development; large-scale data analysis; C++ and Python engineering; safety and validation strategy; architecture decisions; and cross-functional collaboration. The role also provides technical leadership through design reviews, code reviews, mentoring, and engineering best practices.

Develop production-ready real-time C++ software connecting autonomous vehicle systems with mission control, remote assistance, routing, and truck management platforms. Design architectures, algorithms, telemetry, testing frameworks, and verification artifacts for safety-critical vehicle guidance and monitoring. Collaborate across software, systems, perception, controls, and safety teams; support simulation, integration, performance improvements, and automotive standards. Mentor peers and contribute to route planning and machine learning integration for autonomous trucks.

Reviews and audits high-definition map datasets for accuracy, completeness, and safety-critical defects. Performs quality control on geospatial data derived from LiDAR, imagery, and vehicle sensors; documents and triages issues; defines QC metrics, sampling strategies, and repeatable workflows; collaborates with mapping engineers, autonomy teams, and vendors; analyzes defect trends; maintains procedures; and supports launch readiness for new corridors and operational domains.

Lead on-truck integration and bring-up of embedded compute platforms, sensors, networking, vehicle interfaces, and software releases. Own integration readiness, root-cause investigations, validation environments, automation frameworks, system-level test strategies, and technical documentation. Partner across hardware, software, systems, and autonomy teams to improve integration quality and scalability. Mentor engineers and support architecture decisions through lab and field evidence.