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Umanist Staffing LLC

Senior Data Scientist – ML, GenAI &amp; 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
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Design, develop, and deploy machine learning models for complex business problems.
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Apply traditional ML techniques including classification, regression, forecasting, anomaly detection, feature engineering, and model evaluation.
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Build and productionize LLM and Generative AI solutions.
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Develop Agentic AI workflows using technologies such as LangGraph, LangChain, MCP, tool calling, and agent orchestration.
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Design and implement production-grade RAG solutions, including vector databases, hybrid retrieval, reranking, and knowledge graphs.
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Work with AWS Bedrock or comparable enterprise GenAI cloud platforms.
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Analyze large and complex datasets using Python, SQL, and modern data platforms.
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Collaborate with product managers, engineers, customers, and cross-functional stakeholders.
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Communicate architecture decisions, model performance, trade-offs, and recommendations to both technical and non-technical audiences.
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Support production deployment, monitoring, evaluation, and continuous improvement of AI/ML systems.
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Mentor junior data scientists and contribute to technical best practices.
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Required Skills
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5–7 years of relevant Data Science / Machine Learning experience.
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Strong hands-on traditional ML/Data Science background.
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Strong Python and SQL skills.
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Experience with ML frameworks such as Scikit-learn, XGBoost, CatBoost, TensorFlow, or PyTorch.
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12+ months of recent, continuous hands-on GenAI/LLM experience.
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Proven production deployment of AI/ML or GenAI systems.
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Hands-on Agentic AI production experience, including one or more of:
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LangGraph
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LangChain
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MCP
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Tool calling
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Agent orchestration
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Strong RAG implementation experience, including:
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Vector databases
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Hybrid retrieval
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Reranking
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Knowledge graphs
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AWS Bedrock experience strongly preferred.
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Azure OpenAI or Google Vertex AI may be considered as alternate GenAI cloud experience.
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Experience with big data technologies such as Spark/Hadoop.
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Experience with Databricks and/or Snowflake is preferred.
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Experience with LLMOps, evaluation, monitoring, or AI evaluation tooling is a plus.
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Strong communication and client-facing/consulting skills.
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Preferred Domain Experience
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Energy / Utilities / Oil &amp; Gas
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Enterprise technology
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Consulting
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Large-scale enterprise products
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