ML Ops Engineer - Onsite Contract in Pleasanton

Net2Source (N2S)

Pleasanton (CA)

On-site

USD 89,544 - 96,432

Full time

14 days+
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Job summary

A leading IT services provider is seeking an experienced AI/ML Ops Engineer to design and maintain ML Ops pipelines. The role requires strong proficiency in AI/ML operations, project delivery best practices, and a solid foundation in data engineering. Successful candidates will work collaboratively with cross-functional teams to ensure successful model deployment and integration. This position is contract-based located in Pleasanton, California.

Qualifications

  • 5+ years of experience in AI/ML Ops or related areas.
  • Proficiency in ML pipeline tools such as MLflow, or similar.
  • Experience with containerization and orchestration tools (Docker, Kubernetes).
  • Strong programming skills in Python (preferred) or similar languages.
  • Good understanding of model lifecycle management and monitoring practices.
  • Solid foundational knowledge in data engineering concepts (e.g., ETL, data lakes, streaming).

Responsibilities

  • Design, build, and maintain ML Ops pipelines for model training, validation, deployment, and monitoring.
  • Collaborate with data scientists, engineers, and DevOps teams to ensure seamless model integration.
  • Implement CI/CD practices tailored for ML workflows.
  • Monitor and optimize model performance in production environments.
  • Support governance, versioning, and reproducibility of models and datasets.
  • Assist in automating data ingestion, transformation, and validation pipelines.

Skills

AI/ML Operations
Data Engineering
Model Performance Optimization
Python
ML Pipeline Tools
CI/CD Practices
Docker
Kubernetes
Cloud Platforms (AWS, GCP, Azure)
Agile Methodologies

Tools

MLflow
AWS
GCP
Azure

Job description

A leading IT services provider is seeking an experienced AI/ML Ops Engineer to design and maintain ML Ops pipelines. The role requires strong proficiency in AI/ML operations, project delivery best practices, and a solid foundation in data engineering. Successful candidates will work collaboratively with cross-functional teams to ensure successful model deployment and integration. This position is contract-based located in Pleasanton, California.
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