Description

You own the design, building, and deployment of production-ready Generative AI applications and APIs on GCP.

This role is on-site.

Responsibilities

• Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and unstructured data sources.
• Develop and manage end-to-end MLOps pipelines for training, evaluation, deployment, and monitoring.
• Optimize model performance through fine-tuning, prompt engineering, and compression techniques.
• Architect scalable, secure GCP infrastructure with focus on IAM and VPC design.
• Provide technical leadership and mentorship to the engineering team.

Required Skills

• 5–8+ years of industry experience in Machine Learning.
• 3+ years of hands-on experience building and deploying Generative AI/LLM solutions in production.
• Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Advanced experience with Google Cloud Platform, including Vertex AI, BigQuery, and Dataflow.
• Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, or Hugging Face.
• Solid understanding of SQL and unstructured data processing.
• Experience with Docker, Kubernetes (GKE), and CI/CD pipelines.

Preferred Skills

• Experience with multi-agent systems and orchestration (LangGraph, AutoGen).
• Deep understanding of vector databases (Vertex AI Vector Search, Pinecone, Chroma).

Key Skills

Education

Any Gradute