Lead Data Scientist (Gen AI/ML) - Charlotte, NC (Locals)

Lead Data Scientist (Gen AI/ML) - 2 open - Hybrid onsite in Charlotte, NC (candidates must currently be located in Charlotte, NC area or willing to relocate to be onsite from day one)

Position Type: 12 month Contract position with strong possibility of extension.

Interview Process: 4 to 5 rounds (Virtual)

Dislikes on Resumes:

• Generic ML experience without any LLM, agentic, or applied AI work.
• Heavy reliance on low-code/no-code ML platforms without demonstrated software engineering capability.
• Lack of hands-on involvement in end-to-end model deployment or evaluation.

Below are the MUST have Non-Negotiable Required Skills:

• Hands-on experience with LLMs, including prompt engineering, fine-tuning, or agentic architectures (LangGraph, AutoGen, CrewAI, etc.).
• Strong programming skills in Python, with experience in building scalable ML/AI applications.
• Model evaluation expertise for LLM-based systems, including designing metrics and running A/B tests or offline experiments.
• Agentic or Applied AI work
• Very strong Python experience
• LangChain / LangGraph / CrewAI / AutoGen (any relevant)
• Hugging Face Transformers
• Vector DBs (e.g., FAISS, Weaviate, Pinecone)
• Git, VS Code, and cloud platforms (Google Cloud Platform preferred)

Highly Preferred Skills

• Experience with retrieval-augmented generation (RAG) and knowledge graphs, vector Databases.
• Retail or digital experience.
• Designing custom evaluation pipelines for hallucination detection, factual consistency, and user relevance.
• Familiarity with frameworks like TruLens, Ragas, Promptfoo, or ReAct-style evaluation loops.
• Implementing guardrails to ensure safety, compliance, or brand alignment in LLM outputs.
• Prior exposure to PhD-level research or applied LLM work in industry or academia.

Day to Day Responsibilities

• Contribute to the development of a Knowledge Assistant for the Pro & Services organization, with a focus on natural language understanding and agentic workflows.
• Build, evaluate, and iterate on LLM-powered agents to support task execution, reasoning, and retrieval across structured and unstructured data.
• Collaborate closely with product managers, engineers, and other data scientists to integrate intelligent systems into customer and associate-facing platforms.
• Own model evaluation and validation pipelines, especially for LLM and RAG workflows, including performance tracking and ablation studies.
• Write clean, production-grade Python code and contribute to reusable components and pipelines.
• Apply critical thinking and analytical problem-solving to identify patterns, define rules, and optimize agent behaviors.

Any additional details:

• This position will join a high-impact, fast-moving team driving AI innovation for Pro & Services customers. The focus will be on leveraging emerging LLM technologies to simplify and personalize complex retail workflows. A self-starter mindset, curiosity, and the ability to navigate ambiguity are key traits for success.