Senior Data Engineer

Your Role

• such as intelligent assistants, autonomous infrastructure, anomaly detection, recommendation systems, and more.
• Contribute to and/or lead initiatives to fine-tune and optimize LLMs (e.g., LLaMA, Mistral, GPT) using Nutanix-specific datasets.
• Work on RAG pipelines, embeddings, vector DBs, prompt engineering, and responsible AI guardrails.
• Collaborate with product managers, designers, and platform engineers to integrate AI features seamlessly into Nutanix products.
• Own the end-to-end ML lifecycle: from data engineering, experimentation, training, and evaluation to deployment and monitoring.
• Build reusable ML components, services, and APIs with a focus on scalability, observability, and reliability.
• Contribute to internal AI platforms/tools and best practices, including model evaluation frameworks and GPU/accelerator optimization.
• Stay on top of emerging AI/ML research and tools and help drive innovation across the org.

What You Will Bring

Basic Requirements (IC3/IC4)

• Bachelors or Master s in Computer Science, Machine Learning, or related field.
• 3-6 years (IC3) or 6-9 years (IC4) of industry experience in AI/ML with at least 1-2 years in Generative AI and LLMs.
• Strong programming skills in Python, familiarity with ML/AI libraries (PyTorch, TensorFlow, Hugging Face, LangChain, etc.).
• Experience with fine-tuning LLMs, prompt engineering, embeddings, and working with vector databases (e.g., FAISS, Pinecone, Weaviate).
• Hands-on experience in ML Ops: data versioning, model serving, and monitoring.
• Solid understanding of NLP techniques, Transformers, and encoder-decoder architectures.
• Familiarity with cloud-native architectures, Kubernetes, and scalable inference platforms (e.g., Triton, vLLM).