Machine Learning Engineer (Neo4j)

Position: Machine Learning Engineer – Graph AI/Neo4j

Location: Hyderabad, India - Onsite - 5 days a week

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