HYbrid: MLOps Engineer, 3 days onsite 2 days remote

Title : MLops Engineer

Duration: 12 months contract

Location: Sunnyvale, CA ( 3 days onsite 2 days remote )

Required Skills:

Overview

We are seeking a skilled Machine Learning Engineer with strong MLOps capabilities to help design, build, and scale machine learning systems from development through production. This role focuses on operationalizing models, building reliable infrastructure, and supporting data scientists in deploying and maintaining machine learning solutions.

Qualifications

Required

• Strong proficiency in end-to-end machine learning engineering, including data preparation, feature pipelines, deployment, and monitoring.
• Hands-on experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or similar.
• Backend or full-stack development experience with one or more languages (Python, Java, JavaScript/Node, Go, etc.).
• Familiarity with cloud environments (AWS, Google Cloud Platform, Azure) and containerization (Docker, Kubernetes).
• Experience building automated CI/CD pipelines for ML workflows.
• Strong understanding of model versioning, reproducibility, and experiment tracking.
• Ability to work in a fast-paced environment and collaborate across data science, engineering, and product teams.

Preferred

• Experience building internal ML platforms or developer tools.
• Knowledge of distributed systems and large-scale data processing (Spark, Flink, Beam, etc.).
• Familiarity with monitoring tools for ML models (e.g., Evidently AI, Fiddler, Arize, WhyLabs).
• Experience deploying multiple models in production environments.