Design, build, and maintain end-to-end MLOps and LLMOps pipelines covering experimentation, training, deployment, monitoring, and retraining.
Operationalize ML and LLM models for production environments with high availability and scalability.
Implement best practices for model versioning, artifact management, and reproducibility.
Develop and maintain CI/CD/CT pipelines for ML and GenAI workloads.
Monitor model performance, data drift, and model drift in production environments.

Bachelors / master’s degree in data science, AI, Gen AI, or AI/ML.
Strong programming experience in Python.
Experience building REST APIs for ML/AI services using Flask, FastAPI, or similar frameworks.
Solid understanding of MLOps principles, including model lifecycle management and automation.
6-12 years of hands-on experience in Machine Learning with strong operationalization and production delivery exposure.

Continuous learning: You’ll develop the mindset and skills to navigate whatever comes next.
Success as defined by you: We’ll provide the tools and flexibility, so you can make a meaningful impact, your way.
Transformative leadership: We’ll give you the insights, coaching and confidence to be the leader the world needs.
Diverse and inclusive culture: You’ll be embraced for who you are and empowered to use your voice to help others find theirs.

Senior AI ML Ops Engineer

Key skills