From the code to the road, autonomous vehicle leader Torc Robotics relies on a commitment to technical and personal excellence when developing the software tools that will lead to a safer tomorrow. Guided by its three core values of “hungry, humble and people smart,” the early adopters of driverless technology recognize that technical prowess is only part of the equation. “What excites me most about working at Torc is the value add we have on saving lives,” said Engineering Manager Akila Panneerselvam, whose work focuses on vision algorithm development and machine learning. “We aren’t just working on fascinating technology and tools. Even though we’re in artificial intelligence, our work has a real impact on human life.”
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Artificial Intelligence • Automotive • Robotics • Software • Transportation
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.
Artificial Intelligence • Automotive • Robotics • Software • Transportation
Design and implement scalable mapping data-processing pipelines, APIs, and navigation systems for autonomous trucks. Translate ambiguous requirements into technical designs, build high-throughput services, collaborate with consuming engineering teams, incorporate feedback into shipped features, and debug complex software defects. The role requires programming expertise, AWS experience, strong technical communication, independent problem-solving, and familiarity with source control and agile workflows.
Artificial Intelligence • Automotive • Robotics • Software • Transportation
Own system-level simulation testing and virtual verification of autonomous driving software. Plan test campaigns, develop scenarios and test procedures, maintain scenario libraries, identify testing gaps, improve simulation toolchains, analyze results, and communicate dashboards and reports to stakeholders. Support development and integration teams through troubleshooting, fault isolation, and system-level analysis while helping improve autonomous vehicle safety and robustness.
