Description

Lead the design, build, and maintenance of production-grade Generative AI applications and APIs on GCP.

This role is on-site.

Responsibilities

• Build and deploy Generative AI models and LLMs using Gemini, RAG architectures, and vector databases.
• Develop automated MLOps pipelines for training, evaluation, and deployment using Vertex AI, Kubeflow, Cloud Build, and Terraform.
• Optimize model performance through fine-tuning, quantization (GPTQ, AWQ), and prompt engineering.
• Partner with Data Science and Product teams to translate business requirements into technical AI/ML roadmaps.
• Ensure compliance with data privacy, security regulations (HIPAA, GDPR), and ethical AI standards.

Required Skills

• 5-8+ years of industry experience in Machine Learning.
• 3+ years of hands-on experience building and deploying Generative AI models and LLMs in production.
• Strong expertise in Python, scikit-learn, TensorFlow, and PyTorch.
• Proven experience with Google Cloud Platform (GCP) and its AI suite (Vertex AI, BigQuery, Dataflow, Cloud Run).
• Hands-on experience with LangChain, LlamaIndex, or Hugging Face.
• Strong understanding of SQL and unstructured data management.
• Familiarity with Docker, Kubernetes (GKE), and CI/CD tools.

Preferred Skills

• Experience with multi-agent systems and orchestration (e.g., LangGraph, AutoGen).
• Deep knowledge of Vector Databases (e.g., Vertex AI Vector Search, Pinecone, Chroma).
• Google Cloud Professional Machine Learning Engineer certification.

Key Skills

Education

Bachelor's degree