Senior AI Data Scientist

Role Profile:
Senior AI Data Scientist (Internal AI & Infrastructure)

Location:

San Jose, CA Onsite

Contract

Senior Data Scientist with over 12 years of experience specializing in production-grade GenAI and Machine Learning systems within complex enterprise environments. Expert at architecting LLM-powered assistants and predictive models that streamline internal operations, reduce technical debt, and drive measurable ROI. Proven capability in deploying high-performance AI solutions on Kubernetes and distributed cloud architectures to automate internal workflows and diagnostic processes.

• Internal Product Innovation:
  Transform large-scale internal data (logs, tickets, telemetry) into production-ready GenAI solutions to support the Nutanix mission and enhance employee productivity.
• Infrastructure-Aware AI:
  Design and champion AI models that balance immediate internal feature requests against the long-term technical health of Nutanix’s production environments.
• Strategic AI Consulting:
  Partner with Nutanix stakeholders to identify high-impact AI opportunities, demonstrating how data science can optimize internal department OKRs.
• Advanced Analytics:
  Deliver production-ready models for internal resource forecasting, system health monitoring, and automated fault diagnosis.
• Rigorous Evaluation:
  Implement evaluation frameworks using RAGAS and Deep Eval to ensure internal AI tools meet strict accuracy and latency standards.

• GenAI Stack: RAG, Lang Graph, Langfuse, Semantic Search, Re‑ranking, and Vector Databases (Open Search).
• ML & Statistics:
  Expert mastery of Regression, Clustering, and Neural Networks, with the ability to design controlled experiments and A/B tests.
• NLP Expertise: BERT, Transformers, and RASA (DIET Classifier) for building sophisticated internal conversational interfaces.
• Dev Ops & Infrastructure:
  Professional experience with Kubernetes, Helm, Microservices, and REST APIs to ensure AI models are seamlessly integrated into the Nutanix ecosystem.

Education:

Bachelors or Masters in Data Science, Computer Science.
Seniority: 10+ years of end-to-end ML delivery in production.
Interview Ready:
Prepared for deep‑dive technical sessions, including live whiteboarding of AI architectures and statistical modeling.