Senior Data Scientist - ML + GenAI / Agentic AI

Senior Data Scientist – ML, GenAI & Agentic AI

Location: Santa Clara, CA
Experience: 5–7 years relevant experience
Employment Type: Full-Time

About the Role:

This is not a research-only or GenAI exploration role. We are looking for an experienced practitioner who has built and deployed AI/ML solutions in production , can work closely with product and engineering teams, and can confidently communicate technical concepts and architecture decisions to customers and non-technical stakeholders.

Experience in the energy domain is highly preferred .

Key Responsibilities

• Design, develop, and deploy machine learning models for complex business problems.

• Apply traditional ML techniques including classification, regression, forecasting, anomaly detection, feature engineering, and model evaluation.

• Build and productionize LLM and Generative AI solutions.

• Develop Agentic AI workflows using technologies such as LangGraph, LangChain, MCP, tool calling, and agent orchestration.

• Design and implement production-grade RAG solutions , including vector databases, hybrid retrieval, reranking, and knowledge graphs.

• Work with AWS Bedrock or comparable enterprise GenAI cloud platforms.

• Analyze large and complex datasets using Python, SQL, and modern data platforms.

• Collaborate with product managers, engineers, customers, and cross-functional stakeholders.

• Communicate architecture decisions, model performance, trade-offs, and recommendations to both technical and non-technical audiences.

• Support production deployment, monitoring, evaluation, and continuous improvement of AI/ML systems.

• Mentor junior data scientists and contribute to technical best practices.

Required Skills

• 5–7 years of relevant Data Science / Machine Learning experience.

• Strong hands-on traditional ML/Data Science background.

• Strong Python and SQL skills.

• Experience with ML frameworks such as Scikit-learn, XGBoost, CatBoost, TensorFlow, or PyTorch .

• 12+ months of recent, continuous hands-on GenAI/LLM experience .

• Proven production deployment of AI/ML or GenAI systems.

• Hands-on Agentic AI production experience , including one or more of:

  • LangGraph

  • LangChain

  • MCP

  • Tool calling

  • Agent orchestration

• Strong RAG implementation experience, including:

  • Vector databases

  • Hybrid retrieval

  • Reranking

  • Knowledge graphs

• AWS Bedrock experience strongly preferred.

• Azure OpenAI or Google Vertex AI may be considered as alternate GenAI cloud experience.

• Experience with big data technologies such as Spark/Hadoop.

• Experience with Databricks and/or Snowflake is preferred.

• Experience with LLMOps, evaluation, monitoring, or AI evaluation tooling is a plus.

• Strong communication and client-facing/consulting skills.

Preferred Domain Experience

• Energy / Utilities / Oil & Gas

• Enterprise technology

• Consulting

• Large-scale enterprise products