Mid-Senior MLOps Engineer

Compare your skills with our requirements

We are hiring an experienced and systems-oriented MLOps Engineer to build infrastructure for our AI-driven multi-agent recommendation platform. You will manage the lifecycle of ML models and agents to ensure experimentation, deployment, and scalability.

Must-have

• Bachelor’s or Master’s in CS, ML Engineering, or a related field.
• 3+ years of experience in MLOps or ML platform engineering.
• Proficiency in Python and infrastructure-as-code tools.
• Experience with Docker, Kubernetes, and cloud ML platforms.
• Deep knowledge of CI/CD for ML workflows.
• Familiarity with model tracking and serving frameworks.

Is a plus

• Experience supporting modular AI agent architectures.
• Knowledge of distributed frameworks like Ray or Dask.
• Understanding of secure ML infrastructure.
• Experience with model lifecycle, retraining, and versioning.

What you will do

• Design infrastructure for modular ML components.
• Build CI/CD pipelines for model deployment.
• Set up observability and experiment tracking.
• Manage model artifacts and metadata securely.
• Develop orchestration using Airflow, Kubernetes, or Prefect.
• Collaborate across engineering teams for model scaling.