AI/ML Full Stack Developer

Nutanix is a technology company specializing in cloud software and hyper-converged infrastructure. They are seeking an AI/ML Full Stack Developer to design, develop, and deploy machine learning solutions for their education platform, focusing on neural recommendation systems and conversational AI agents.

Responsibilities

• Participate in ML sprint planning, including model experimentation roadmaps, RAG pipeline optimization, agentic workflow design, feature engineering discussions, and training pipeline estimations
• Design, develop, and deploy machine learning models, RAG systems with vector databases and embedding models, and autonomous AI agents with tool calling capabilities, ensuring scalability, latency optimization, and alignment with business objectives
• Conduct peer reviews of ML code, RAG retrieval strategies, agent framework implementations, model architectures, and experiment results, contributing to team-wide evaluation of semantic search quality, agent performance, and model benchmarking
• Mentor junior ML engineers on best practices in model development, RAG architecture patterns, building multi-agent systems, prompt engineering, hyperparameter tuning, data preprocessing, and production ML systems
• Monitor deployed models, RAG pipelines, and agentic workflows in production, manage embedding model updates, optimize retrieval performance, debug agent behavior, handle model drift detection, and maintain MLOps infrastructure for continuous delivery
• Collaborate effectively with distributed ML teams across time zones, coordinating on shared vector stores, agent orchestration frameworks, model serving infrastructure, and cross-functional AI initiatives
• Stay current with latest ML research, RAG optimization techniques, agentic AI frameworks like LangGraph and AutoGen, emerging model architectures, fine-tuning techniques, and GenAI advancements, bringing innovative approaches to team discussions and technical implementations
• Document model architectures, RAG system designs, agent workflows, retrieval strategies, training procedures, feature specifications, and deployment processes through model cards, experiment tracking logs, architecture diagrams, and comprehensive ML documentation to enable reproducibility and knowledge transfer

Skills

• Bachelor's degree in Computer Science, Machine Learning, Data Science, or related technical field with solid foundation in Python and familiarity with ML frameworks (PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers)
• Experience or strong interest in building ML systems with understanding of model training, fine-tuning, and deployment concepts
• Familiarity with modern AI/ML approaches including working with LLMs, prompt engineering, RAG systems using vector databases and embeddings, or agentic AI frameworks like LangGraph, LangChain, or AutoGen
• Understanding of NLP concepts, semantic search, and retrieval strategies
• Ability to work in Agile environments with willingness to learn, experiment, iterate on models, and take ownership of assigned ML projects and features
• Strong communication skills, eagerness to learn from senior team members, and enthusiasm for contributing ideas, staying current with ML research, and growing as an AI/ML engineer
• Exposure to MLOps practices like experiment tracking, model versioning, or containerization is a plus
• Experience with GPU infrastructure or optimizing model serving is beneficial but not required

Benefits

• Sign-on bonus
• Restricted stock units
• Discretionary awards
• Full range of medical benefits
• Financial benefits
• 401(k) eligibility
• Various paid time off benefits
• Vacation
• Sick time
• Parental leave

Company Overview

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