Software Engineer II, MLOps Framework

Torc Robotics

2d • $139,000 - $166,800

About The Position

As a Software Engineer on the ML Ops Framework & Conversion team, you will own the pipelines that take models from research to production on edge hardware, including model conversion, compilation, benchmarking, and release. Our team is comprised of engineers with deep expertise in ML and RL frameworks, embedded systems, and autonomous driving — united by a focus on getting models from development into the real world reliably and at scale.
The ML Ops Framework & Conversion team is responsible for the full model conversion process — from architecting TensorRT pipelines to maintaining the model release registry across platforms. In this role, you will work closely with perception and safety teams to ensure every model that ships meets strict latency and accuracy requirements for autonomous trucking.

Requirements

• Bachelor's Degree in Computer Science, Electrical Engineering, Robotics, or related field plus 4+ years of relevant experience; or Master's Degree plus 2+ years.
• 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.

Nice To Haves

• 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.

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.

Benefits

• A competitive compensation package that includes a bonus component and stock options
• 100% paid medical, dental, and vision premiums for full-time employees
• 401K plan with a 6% employer match
• Flexibility in schedule and generous paid vacation (available immediately after start date)
• AD+D and Life Insurance

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level