ML Engineer: Scalable Multimodal Inference & Featurization

General Motors; Sunnyvale (CA); On-site; USD 117,700 - 221,400; Full time

Job summary

General Motors is seeking a hands-on machine learning engineer to build data processing, featurization, and inference foundations for scalable world understanding. The role spans ML systems, production infrastructure, and evaluation loops, turning ambiguous problems into practical, reliable solutions.

You’ll collaborate with ML, infrastructure, and evaluation teams to deliver robust data processing, scalable pipelines, and production-ready features that accelerate experimentation and deployment.

Qualifications

• BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or related field or equivalent practical experience.
• Experience building production data processing or machine learning pipelines at scale.
• Experience with featurization, embedding, inference, or retrieval systems for vision or multimodal workloads.
• Strong understanding of computer vision models and deploying them in production.
• Experience evaluating ML systems using clear metrics, experiments, and regression safeguards.
• Proven ability to work hands-on in fast-moving environments with incomplete information.
• Strong ownership mindset and ability to drive execution through ambiguity.

Responsibilities

• Design, build, and productionize data processing and featurization pipelines for large-scale multimodal data
• Improve inference frameworks for computer vision and multimodal models with a focus on reliability and simplicity
• Drive scalability and cost efficiency across the end-to-end pipeline (compute, throughput, storage, query)
• Collaborate with partners across ML, infrastructure, and evaluation to enable rapid experimentation and production use
• Develop and refine evaluation methods for model quality, retrieval quality, and system-level performance
• Provide strong technical judgment and clear execution plans to move from prototype to production
• Take ownership of ambiguous problems and define practical paths forward with urgency

Skills

Production ML pipelines

Hands-on engineering

Computer vision

Ambiguity tolerance

Ownership mindset

Metrics-driven evaluation

Featurization

Job description

General Motors is seeking a hands-on machine learning engineer to build data processing, featurization, and inference foundations for scalable world understanding. The role spans ML systems, production infrastructure, and evaluation loops, turning ambiguous problems into practical, reliable solutions.

You’ll collaborate with ML, infrastructure, and evaluation teams to deliver robust data processing, scalable pipelines, and production-ready features that accelerate experimentation and deployment.