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Graph Machine Learning Engineer Job Opening In Hyderabad – Now Hiring Circuitry.ai


Job description

Position: Machine Learning Engineer – Graph AI/Neo4j


Location: Hyderabad, India - Hybrid Remote (3 days in office, 2 days remote)

Experience: 2+ years

Employment Type: Full-time


Position Overview:

We are seeking a talented and experienced Machine Learning Engineer with a strong background in graph databases, particularly Neo4j, to join our dynamic team.

The ideal candidate will be instrumental in developing and enhancing our knowledge bases and Retrieval-Augmented Generation (RAG) models, driving the accuracy and efficiency of our AI-powered solutions.

You will play a key role in deploying cutting-edge models that enhance the AI features of our end-user applications, ensuring they meet the evolving needs of our customers.


Key Responsibilities

  • Develop and support machine learning models with a focus on graph-based data and Neo4j.
  • Build and maintain Python scripts and data pipelines for processing and analyzing graph data.
  • Work with Large Language Models (LLMs) and retrieval-augmented generation (RAG) techniques as part of the ML workflow.
  • Collaborate with backend and data teams to integrate graph AI solutions into applications.
  • Write clean, reusable code and participate in code reviews.
  • Support deployment and basic monitoring of ML models in production.
  • Document workflows and solutions for team knowledge sharing.


Must-Have Qualifications

  • 2+ years of experience in Machine Learning or Data Science using Python.
  • Experience working with at least one graph database (preferably Neo4j) for data modeling and basic queries.
  • Good understanding of machine learning fundamentals (regression, classification, basic model evaluation).
  • Exposure to using or integrating LLMs (OpenAI, HuggingFace, or similar) with data workflows.
  • Basic knowledge of retrieval-augmented generation (RAG) concepts.
  • Familiarity with Python data libraries (pandas, scikit-learn, etc.).
  • Ability to work with RESTful APIs.
  • Familiarity with version control (Git) and writing simple unit tests.


Nice to Have

  • Hands-on experience building or optimizing graph ML models (e.G., node classification, link prediction).
  • Exposure to vector search or hybrid search techniques.
  • Experience deploying Python code or ML models using Docker or basic cloud services (AWS, GCP, Azure).
  • Experience working in a SaaS or multi-tenant application environment.


Key Skills

Python, Machine Learning, Graph Databases (Neo4j), LLM, RAG, Data Pipelines, Git, REST API

Required Skill Profession

Computer Occupations


  • Job Details

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Unlock Your Graph Machine Potential: Insight & Career Growth Guide


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