Machine Learning Engineer

2 weeks ago


Hyderabad, India Circuitry.ai Full time

Position: Machine Learning Engineer – Graph AI/Neo4jLocation: Hyderabad, India - Hybrid Remote (3 days in office, 2 days remote)Experience: 2+ yearsEmployment Type: Full-timePosition 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 SkillsPython, Machine Learning, Graph Databases (Neo4j), LLM, RAG, Data Pipelines, Git, REST API



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