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
Leads development of BEV and multi-modal perception models for autonomous trucks, combining camera, LiDAR, radar, and HD map data. Responsibilities include model architecture, large-scale distributed training, data pipelines, robustness evaluation, sensor fusion, research into foundation models, and mentoring ML engineers. The role requires deep expertise in 3D vision, autonomous systems, multi-view fusion, and production-scale machine learning.
Artificial Intelligence • Automotive • Robotics • Software • Transportation
Develop and deploy production machine learning models and sensor-fusion algorithms for autonomous-truck ego-motion estimation and localization. Build scalable PyTorch training workflows, analyze large vehicle datasets, and create robust C++ and Python production software. Define validation strategies, optimize performance under real-time constraints, make architecture decisions, and collaborate across autonomous-driving teams. Provide technical leadership through design reviews, code reviews, mentoring, and engineering best practices.
Artificial Intelligence • Automotive • Robotics • Software • Transportation
Provide on-call MLOps support for machine learning teams by triaging pipeline issues, debugging workflows, identifying root causes, and maintaining reliable model development operations. Collaborate with senior engineers to improve tooling, documentation, and processes, while communicating technical findings across teams. The role requires Python, foundational PyTorch and model pipeline experience, plus familiarity with CI/CD, monitoring, logging, and orchestration tools.
