Senior ML Evaluation & Tooling Engineer

Remote Jobs; Austin (TX); On-site; USD 145,000 - 261,000; Full time

Benefits offered by this job

Health and wellbeing benefits

Relocation benefits

GM vehicle discounts

Job summary

General Motors is seeking a Senior Engineer for the Embodied AI Scaling Foundations group to design, implement, and iterate on evaluation and introspection tools for autonomous vehicle performance.

Remote role with occasional travel up to 25% and relocation benefits; work across Data, Infra, and validation teams to connect offline evaluation with real‑world behavior and drive safer, scalable models.

Qualifications

• 3+ years of relevant industry experience.
• Backend: Python, Node.js, high-throughput data streaming.
• Frontend: React/TypeScript, WebGL/WebGPU (for 3D sensor visualization), Streamlit, Jupyter notebooks.
• Data/Infra: Spark for stream processing, BigQuery, Kubernetes.
• Strong communication skills and ability to collaborate effectively across engineering partners.
• Bachelor's degree in Computer Science or related field or equivalent experience.

Responsibilities

• Build and improve high-quality evaluation signal and introspection tools that help shorten the experimental path towards the best model.
• Develop and maintain visualization and metrics presentation within our model evaluation loop.
• Help teams introspect model behavior and reach actionable next steps with fewer manual steps.
• Participate in design and code reviews and work with Data, Infra, and validation teams to connect offline evaluation with real-world behavior.

Skills

Python

Node.js

Data streaming

React

TypeScript

WebGL

Streamlit

Jupyter

Kubernetes

Communication

Education

Bachelor's degree in Computer Science or related field

Tools

BigQuery

Spark

Job description

General Motors is seeking a Senior Engineer for the Embodied AI Scaling Foundations group to design, implement, and iterate on evaluation and introspection tools for autonomous vehicle performance.

Remote role with occasional travel up to 25% and relocation benefits; work across Data, Infra, and validation teams to connect offline evaluation with real‑world behavior and drive safer, scalable models.