Autonomy ML Engineer — Multimodal Pipelines

Remote; San Francisco (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

Remote in San Francisco is seeking an ML/AI systems engineer to build the software backbone for autonomous-model data pipelines and evaluation workflows. You will own end-to-end model code paths, from input tokenization to deployment, and craft tooling for metrics, observability, and low-latency serving.

The role requires solid Python, production-grade coding, and experience with ML frameworks (PyTorch/TensorFlow/JAX) plus MLOps and CI/CD.

Qualifications

• MS in CS/ML/Robotics or BS with ≥2 years building ML/data/evaluation systems
• Strong Python fundamentals and production-quality code experience
• Experience building ML data and evaluation pipelines
• Experience with PyTorch, TensorFlow, or JAX
• Experience with large multimodal datasets and data integrity checks
• Familiarity with MLOps, CI/CD, and observability
• Excellent communication and ownership in a small team

Responsibilities

• Design and ship multimodal data pipelines and reproducible training/evaluation workflows
• Implement and iterate on LLM, VLM, and VLA architectures; own model code paths, input/tokenization, inference
• Integrate simulators for closed-loop evaluation; build tooling for metrics, visualization, and experiment management
• Deliver production-grade serving and inference tooling for deterministic, low-latency operation
• Own systems from scratch: architecture - implementation - testing - documentation - iteration

Skills

Python

Production-grade code

ML pipelines

Training & serving

MLOps

Communication

Education

MS in CS/ML/Robotics or BS + ≥2 years

Tools

PyTorch

TensorFlow

JAX

CI/CD

Job description

Remote in San Francisco is seeking an ML/AI systems engineer to build the software backbone for autonomous-model data pipelines and evaluation workflows. You will own end-to-end model code paths, from input tokenization to deployment, and craft tooling for metrics, observability, and low-latency serving.

The role requires solid Python, production-grade coding, and experience with ML frameworks (PyTorch/TensorFlow/JAX) plus MLOps and CI/CD.