ML Engineer - MLOps

Job Summary

Take machine-learning and LLM models from notebooks to reliable, monitored production systems.

Responsibilities

• Build training, evaluation and deployment pipelines
• Implement model versioning, registries and CI/CD for models
• Deploy models as scalable APIs or batch jobs
• Monitor drift, quality and cost in production
• Collaborate with data scientists and platform teams

Requirements

• 3-6 years of ML engineering or software engineering experience
• Strong Python and ML framework experience
• Experience with MLOps tools (MLflow, SageMaker, Azure ML or Kubeflow)
• Containerisation and cloud deployment experience

Nice to have

• LLMOps experience
• Spark or Databricks
• Feature stores

Tech stack

• Python
• PyTorch
• MLflow
• Amazon SageMaker
• Azure Machine Learning
• Kubeflow
• Docker
• Kubernetes

What we offer

• A permanent, full-time role
• Enterprise projects for clients in the US and worldwide
• Hands-on work across AI, cloud and modern engineering
• A friendly, collaborative team
• Clear paths for professional growth

Work authorization

This role is based in Hyderabad, India. Applicants must be legally eligible to work in India.