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Machine Learning & Generative AI Engineer (2-5 years of experience only required)
Machine Learning & Generative AI Engineer (2-5 years of experience only required)Nisum • San Jose, CA, United States
Machine Learning & Generative AI Engineer (2-5 years of experience only required)

Machine Learning & Generative AI Engineer (2-5 years of experience only required)

Nisum • San Jose, CA, United States
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Overview

Machine Learning & Generative AI Engineer (2-5 years of experience only required)

Pay found in job post.

Base pay range : $30.00 / hr - $40.00 / hr

What You’ll Do

  • We are seeking a Machine Learning & Generative AI Engineer with strong expertise in the Azure ecosystem and Databricks, combined with experience in Generative AI (GenAI), Retrieval-Augmented Generation (RAG), and agentic systems with tool use.
  • The ideal candidate will be comfortable designing and deploying ML and GenAI systems end-to-end, including classical ML models, deep learning solutions, and modern agent frameworks.
  • Design, implement, and optimize ML and GenAI pipelines on Azure Databricks.
  • Build and deploy RAG systems and agentic AI systems with tool use for enterprise applications.
  • Work with Model Context Protocol (MCP) and AI Development Kit (ADK) to build scalable agentic solutions.
  • Leverage frameworks such as LangChain, LangGraph, LangSmith, and other popular GenAI ecosystems. Conduct EDA, feature engineering, and NAS experiments to improve model performance.
  • Build and optimize regression, classification, and forecasting models using Scikit-learn, XGBoost, PyTorch, and TensorFlow.
  • Utilize GPUs for large-scale model training and inference.
  • Develop, deploy, and monitor models and agents in production environments with proper serving and observability.
  • Collaborate with data engineers, product managers, and stakeholders to integrate GenAI and ML solutions into business workflows.

What You Know

  • Strong experience with Azure Databricks and broader Azure cloud ecosystem (Data Lake, Data Factory, Synapse, etc.).
  • Hands-on expertise in Generative AI (LLMs, RAG, agentic frameworks, tool use).
  • Experience with MCP and ADK for building GenAI and agent workflows.
  • Proficiency with LangChain, LangGraph, LangSmith, and other modern frameworks for orchestration and observability.
  • Solid background in Python, NumPy, Pandas, and ML libraries.
  • Experience in EDA, feature engineering, time-series forecasting, and NAS.
  • Strong knowledge of ML model development (regression, classification, forecasting) and deep learning frameworks (PyTorch, TensorFlow).
  • Familiarity with model serving, MLOps practices, and CI / CD for AI systems.
  • Experience with GPU-enabled ML / GenAI workflows.
  • Prior industry experiences deploying RAG systems and agentic AI workflows in production.
  • Exposure to vector databases, embeddings, and semantic search.
  • Familiarity with observability tools for GenAI pipelines. Strong problem-solving and communication skills with the ability to thrive in cross-functional teams.
  • 5+ years in ML / AI roles is preferred. Junior candidates with strong GenAI / agentic experience and the right mindset are also welcome.
  • Education

  • Bachelor’s degree required
  • Compensation Band

    $30 - $40 per hour

    Seniority level

  • Entry level
  • Employment type

  • Contract
  • Job function

  • Engineering and Information Technology
  • Industries

  • IT Services and IT Consulting
  • #J-18808-Ljbffr

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