Jobs · Engineering · California

AI/ML Tech lead with Gen AI

MACHINE LEARNING TECHNOLOGIES LLC · Rosemead, CA · 2 wk ago
EngineeringContract

About the role

Designing and deploying scalable, secure, and reliable LLM-based solutions, implementing Retrieval-Augmented Generation (RAG), model fine-tuning, and agentic workflows to solve complex business problems.

Key Responsibilities

  • Design, build, and maintain production-grade Generative AI applications and APIs on GCP, focusing on Gemini models, RAG architectures, and vector databases.
  • Develop automated MLOps pipelines (training, evaluation, monitoring, deployment) using Vertex AI, Kubeflow, Cloud Build, and Terraform.
  • Implement techniques to enhance AI model performance, including fine-tuning, quantization (e.g., GPTQ, AWQ), and prompt engineering to improve accuracy and reduce latency.
  • Optimize GCP resources for high-performance computing, ensuring scalability, cost-efficiency, and security (IAM, VPC).
  • Partner with Data Science, Data Engineering, and Product teams to translate business requirements into technical AI/ML roadmaps.
  • Ensure compliance with data privacy, security regulations (HIPAA, GDPR, if applicable), and ethical AI standards.

Required Qualifications

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

Preferred Qualifications

  • 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.
  • Demonstrated experience leading team projects and mentoring junior engineers.

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