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AI & machine learning / UTIS-ML-US-008

Senior ML Engineer (Foundation Model Training & MLOps)

Develop, fine-tune and deploy ML and foundation models at scale for a global semiconductor company, and operate multi-GPU MLOps pipelines on Azure and AKS.

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Region
San Jose or San Diego, California, United States
Work arrangement
Hybrid
Engagement type
Independent contractor with UTIS (1099)
Working hours
Onsite with partial remote work per team arrangement.
Posted
August 24, 2026
Applications
Open until filled
Openings
2

What you will work on

  • Train, fine-tune and deploy ML and foundation models using PyTorch or TensorFlow.
  • Package production models on Azure and AKS and support monitoring and retraining.
  • Build and operate multi-GPU training and inference pipelines.
  • Implement CI/CD, model versioning, registry, promotion, validation, rollback and alerting.
  • Write tested production Python and document reproducible interfaces and operations.
  • Collaborate with ML researchers, data scientists and data, platform and security teams.

What you bring

  • 4+ years of hands-on machine-learning engineering.
  • Production development, training, fine-tuning and deployment of ML and foundation models at scale.
  • Strong Python and PyTorch or TensorFlow.
  • Multi-GPU MLOps pipelines, CI/CD, model lifecycle management and monitoring.
  • Azure and Azure Kubernetes Service deployment experience.
  • Strong testing, code-quality and automation practices.
  • Ability to work onsite in San Jose or San Diego under the team’s hybrid arrangement.

Useful additional experience

  • Distributed training frameworks and large-scale model training.
  • GPU workload management and model performance optimization.
  • ML-platform infrastructure and orchestration.
  • Platform reliability, governance and compliance exposure.
  • Mentoring or technical leadership experience.

Engagement details

  • Long-term engagement.