Sr. Software Integration Engineer, Autonomy

42dot • San Francisco, CA

15h • $200,000 - $300,000

About The Position

42dot is seeking a Senior Software Integration Engineer to connect machine-learning autonomy models with the vehicle’s on-board system. The role focuses on turning models developed by research and ML teams into systems that run reliably and in real time on vehicle hardware. As a founding-team opportunity, the position will help establish the on-board integration architecture, including the model deployment pipeline, inference optimization strategy and tooling, and interface contracts between ML models and on-board software.

Requirements

• A track record of grit and ownership, with success moving difficult problems from ambiguity to successful deployment.
• Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field.
• At least 5 years of experience in systems or software engineering, with meaningful experience in ML inference, embedded systems, or real-time software.
• Experience deploying and optimizing ML models in production, including on resource-constrained hardware.
• Strong C++ and Python skills, with experience working across the ML and systems boundary.

Nice To Haves

• Background in autonomous driving or robotics on-board software.
• Experience with inference optimization frameworks such as TensorRT and ONNX Runtime, and automotive SoCs.
• Experience with real-time operating systems and safety-critical software practices.
• Experience building CI/CD and automated validation pipelines.

Responsibilities

• Integrate ML models, including end-to-end driving, VLA, and world models, onto the on-board compute and runtime stack.
• Optimize model inference for latency, throughput, memory, and power on embedded automotive hardware.
• Build and maintain the model deployment pipeline, including conversion, validation, and rollout.
• Stabilize on-vehicle ML execution by diagnosing runtime failures, timing violations, and resource contention.
• Define interface contracts between ML models and the rest of the on-board software stack.
• Work closely with the ML autonomy team to connect deployment constraints with model design.

What This Job Offers

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