Senior Data Scientist – Generative AI
New
J
JobgetherData Science AI
Based in the United States, Eastern or Central U.S.Full-TimeSenior
Salary$117,600–$161,700
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Job Details
- Experience
- 5+ years with Bachelor’s; 3+ years with Master’s; or PhD-level study
- Required Skills
- PythonMachine LearningSnowflakeAzureDatabricksNLPLLMGenerative AILangChain
Requirements
- Bachelor’s degree with 5+ years of experience, Master’s degree with 3+ years, or PhD-level study in a quantitative discipline.
- Strong proficiency in Python and modern software development practices for AI/ML.
- Experience with text mining, embeddings, transformers, and modern NLP approaches.
- Hands-on expertise with LLM prompt engineering and architectural patterns such as RAG.
- Experience with frameworks like LangChain, LangGraph, AutoGen, or CrewAI.
- Proficiency with cloud and data platforms including Azure, Databricks, GCP, and Snowflake.
- Ability to design, evaluate, and deploy AI applications in production environments.
- Understanding of LLM evaluation methodologies, reliability, safety, and scale trade-offs.
- Knowledge of data governance, privacy, security, and compliance requirements.
- Ability to work within the Eastern or Central U.S. time zones.
- Access to a dedicated workspace and reliable internet service (approx. 25 Mbps down/10 Mbps up).
- Willingness to travel occasionally for training or meetings.
Responsibilities
- Design, develop, and deploy production-ready LLM applications focused on conversational intelligence and insight generation.
- Build multi-step AI workflows incorporating retrieval, orchestration, routing, tool use, and agentic patterns.
- Develop robust evaluation frameworks for LLM applications to measure response quality, reliability, and safety.
- Apply NLP and machine learning techniques to extract insights from conversations, transcripts, and documents.
- Collaborate with data, product, and engineering teams to transition GenAI prototypes into scalable production solutions.
- Develop clean, maintainable Python code following engineering best practices.
- Ensure AI solutions meet enterprise standards for data governance, privacy, security, and compliance.
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