Description

You will build and maintain scalable machine learning infrastructure and data pipelines.

Responsibilities

• Design and implement scalable MLOps data pipelines for ingestion, processing, and storage.
• Deploy models using Vertex Pipelines, Kubeflow, or similar platforms.
• Implement and support end-to-end machine learning workflows and patterns.
• Build AI/ML products using neural networks, LLMs, and RAG techniques.
• Apply supervised tuning and vector database integration to production workflows.

Required Skills

• 5+ years of experience in machine learning or MLOps roles.
• Expert-level Python programming skills.
• Hands-on experience with Vertex Pipelines, Kubeflow, or Vertex AI.
• Proficiency with containerization using Docker and Kubernetes.
• Experience with large-scale frameworks including TensorFlow, PyTorch, Spark ML, or Caffe2.
• Practical knowledge of LangChain or similar orchestrators and Vector DBs.
• Experience with Gen AI technologies including Gemini, OpenAI, Claude, and open-source LLMs.
• Strong understanding of distributed systems and CI/CD practices.
• Development experience with Google Cloud Platform or Google AutoML.

Preferred Skills

• Experience implementing RAG and supervised tuning techniques.

Key Skills

Education

Any Graduate