Software Engineer II, MLOps Framework

Torc Robotics develops software for autonomous trucks and automated driving applications. The Software Engineer II will own model conversion, compilation, benchmarking, and release pipelines that move machine learning models from research into production on edge hardware, while collaborating with perception and safety teams to meet latency and accuracy requirements.

Responsibilities:

• Architect and implement model conversion and compilation pipelines using tools such as ONNX, TensorRT, and torch.compile for deployment on edge devices (e.g., NVIDIA Orin)
• Maintain and evolve the model release registry, ensuring traceability and reproducibility across model versions and target platforms
• Perform rigorous latency benchmarking and model quality parity evaluations to validate that deployed models meet safety-critical performance requirements
• Compare metrics across platforms to verify accuracy and latency compliance before release
• Communicate and collaborate with model development teams and broader stakeholders, ensuring your findings translate into reliable, actionable outcomes across the organization

Requirements:

• Bachelor's Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 4+ years of experience or
• Master's Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 0-3+ years of experience
• Extensive experience with model conversion and compilation pipelines (ONNX, TensorRT, torch.compile) and performing rigorous latency benchmarking and quality parity validation
• Hands-on experience deploying and testing models on edge hardware (e.g., NVIDIA Orin or similar embedded platforms)
• Experience maintaining a model release registry in a production environment
• Ability to compare and interpret performance metrics across hardware platforms to validate models against strict latency and accuracy requirements
• Expertise in model quantization (PTQ, QAT) and mixed-precision inference (INT8, FP8, FP4, BF16/FP16)
• Experience releasing multi-target models across heterogeneous platforms
• Familiarity with SOTA autonomous driving perception algorithms — temporal 3D object detection, BEV, 3D Occupancy Networks — and multi-modal sensor fusion (vision, LiDAR, radar)
• C++ and/or CUDA kernel development