Description

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

This role is on-site.

Responsibilities

• Design and build production-grade Generative AI applications and APIs using Gemini models and RAG architectures.
• Develop automated MLOps pipelines for training, evaluation, monitoring, and deployment using Vertex AI, Kubeflow, Cloud Build, and Terraform.
• Implement model enhancement techniques including fine-tuning, quantization (GPTQ, AWQ), and prompt engineering to optimize accuracy and latency.
• Optimize GCP resources for scalability, cost, and security (IAM, VPC).
• Translate business requirements into technical AI/ML roadmaps by partnering with Data Science, Data Engineering, and Product teams.

Required Skills

• 5-8+ years of industry experience in Machine Learning.
• 3+ years deploying Gen AI models/LLMs in production.
• Strong expertise in Python and data science libraries (scikit-learn, TensorFlow, PyTorch).
• Proven experience with Google Cloud Platform (GCP) and its AI suite (Vertex AI, BigQuery, Dataflow, Cloud Run).
• Hands-on experience with framework tooling like LangChain, Llamaindex, or Hugging Face.
• Strong understanding of SQL and unstructured data management.
• Familiarity with Docker, Kubernetes (GKE), and CI/CD tools.
• Bachelor's degree in Computer Science or related field.

Preferred Skills

• Experience building and deploying models using GCP, Docker, Kubernetes, CI/CD, Scikit-learn, TensorFlow, PyTorch.

Key Skills

Education

Bachelor's degree