Position: Senior Data Scientist – GenAI / Machine Learning
Location: Santa Clara, CA
Job Type: Full-Time | On-Site
Job Summary
We are seeking a Senior Data Scientist with a strong traditional Machine Learning/Data Science background and hands-on production experience with Generative AI, LLMs, RAG, and Agentic AI workflows. The ideal candidate will have experience delivering AI/ML solutions to production and confidently communicating technical concepts to both technical and non-technical stakeholders.
Key Responsibilities
Develop, deploy, and maintain machine learning models for complex business problems.
Build production-grade GenAI/LLM solutions using LangChain, LangGraph, MCP, tool calling, and agent orchestration.
Design and implement RAG solutions using vector databases, hybrid retrieval, reranking, and knowledge graphs.
Apply traditional ML techniques including classification, regression, forecasting, anomaly detection, feature engineering, and model evaluation.
Analyze large and complex datasets to generate actionable business insights.
Collaborate with product managers, engineers, and customers to integrate AI/ML solutions into enterprise products.
Communicate architecture decisions, technical trade-offs, findings, and recommendations to non-technical stakeholders.
Provide mentorship and contribute to data science best practices.
Stay current with advancements in AI, machine learning, LLMs, and data science.
Required Qualifications
5–7+ years of relevant Data Science/Machine Learning experience.
At least 12 months of recent, continuous hands-on GenAI/LLM experience.
Proven production experience deploying AI/ML systems; POC or certification-only experience is not sufficient.
Hands-on Agentic AI experience with LangGraph, LangChain, MCP, tool calling, and agent orchestration.
Strong RAG implementation experience, including vector databases, hybrid retrieval, reranking, and knowledge graphs.
AWS Bedrock experience required. Azure OpenAI or Vertex AI may be considered as alternatives.
Strong traditional ML/DS experience with classification, regression, forecasting, anomaly detection, feature engineering, and model evaluation.
Strong Python or R programming skills.
Experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
Strong SQL and experience working with large datasets.
Excellent communication and client-facing/consulting skills.
Willingness to attend an in-person interview in Santa Clara, CA.
Nice to Have
Energy/utilities industry experience strongly preferred.
Experience with Databricks, Snowflake, XGBoost, or CatBoost.
LLMOps and AI evaluation tooling experience.
Experience with Hadoop, Spark, Tableau, or Power BI.
Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.