Machine Learning Engineer

4 days ago

Lal Bahadur Nagar, India Circuitry.ai Full time

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

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