Description

Architect and build a scalable machine learning platform for training, deployment, and lifecycle management of ML, LLM, and Generative AI models.

This role is on-site.

Responsibilities

• Lead infrastructure development for production hosting of complex AI systems and large-scale inference workloads.
• Design developer-friendly abstractions and automation to simplify model development and deployment processes.
• Implement MLOps capabilities including experiment tracking, model versioning, CI/CD for ML, and monitoring using Databricks and MLflow.
• Serve as technical leader, guiding architecture decisions, design reviews, and engineering best practices.

Required Skills

• 12+ years of experience in machine learning, NLP, and Generative AI systems.
• Extensive experience in MLOps, model lifecycle management, and deployment.
• Proficiency in Databricks and ML platform tools.
• Experience deploying and managing large-scale AI/ML systems.
• Knowledge of Agentic AI and modern AI frameworks.
• Familiarity with LLMs, LangChain Development, and LLM Ops practices.
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.

Preferred Skills

• Strong understanding of cloud-based ML infrastructure and scalable architectures.
• Experience building CI/CD pipelines for machine learning workflows.

Key Skills

Education

Any Graduate