Principal Data Scientist- W2 | Remote

Job Title: Principal Data Scientist Work Arrangement: Remote for the first 6 months, then onsite in Raleigh, NC
Client: LexisNexis

Position Overview

We are seeking a highly experienced Principal Data Scientist to lead the design, development, and deployment of advanced AI/ML and LLM-based systems. The ideal candidate will have strong experience in Data Science, Machine Learning Engineering, Generative AI, and production-grade LLM applications.

The candidate should be capable of working at both the research/architecture level and hands-on implementation level, translating advanced AI techniques into scalable enterprise solutions.

Required Qualifications

• Master's degree or PhD preferred.
• 10 12+ years of experience in Data Science / Machine Learning Engineering.
• Deep hands-on experience with LLM-based systems and Generative AI.
• Strong experience designing and implementing production-grade AI/ML solutions.
• Experience with deep learning, NLP, transformers, and model fine-tuning.
• Strong Python programming and ML engineering experience.
• Experience building and deploying scalable ML/AI systems.

Key Technical Skills

Generative AI / LLM

• Large Language Models (LLMs)
• Generative AI
• LLM application development
• Prompt engineering
• Model evaluation
• Hallucination detection and mitigation
• LLM observability and monitoring

RAG & Retrieval

• Retrieval-Augmented Generation (RAG)
• Embeddings
• Vector databases
• Semantic search
• Hybrid retrieval
• Reranking
• Chunking strategies
• Metadata filtering
• Retrieval optimization

Machine Learning / Deep Learning

• PyTorch
• HuggingFace
• Transformers
• NLP
• Deep learning
• Model fine-tuning
• Classification
• Information extraction
• Summarization
• Question answering

AI Agent Architecture

• Multi-agent architectures
• Planner-executor patterns
• Tool-use agents
• ReAct-style reasoning
• Agent orchestration
• Tool calling
• Workflow routing
• Memory and guardrails

Frameworks & Platforms

• LangChain
• LlamaIndex
• Kubernetes
• Containerized model serving
• Production ML APIs
• Monitoring and observability
• Cloud/production deployment

Data & Vector Technologies

Experience with technologies such as:

• Pinecone
• Weaviate
• FAISS
• Chroma
• pgvector
• Embedding indexes
• Vector retrieval infrastructure

Responsibilities

• Lead the architecture and development of enterprise-scale AI/ML and LLM solutions.
• Design and implement production-grade RAG pipelines.
• Develop and optimize multi-agent AI architectures.
• Build LLM applications using frameworks such as LangChain and LlamaIndex.
• Fine-tune and evaluate transformer-based models.
• Develop evaluation frameworks for model quality, retrieval accuracy, groundedness, latency, cost, and reliability.
• Establish methods for detecting hallucinations and other LLM failure modes.
• Design scalable ML serving and deployment architectures.
• Work with Kubernetes and containerized inference environments.
• Implement monitoring, observability, alerting, and model-performance tracking.
• Collaborate with Data Scientists, ML Engineers, Product teams, and other technical stakeholders.
• Provide technical leadership, architecture guidance, mentoring, and code reviews.
• Translate business requirements into scalable AI/ML solutions.
• Drive AI strategy, technical roadmaps, experimentation, and continuous improvement.

Preferred Experience

• Experience leading principal-level AI/ML architecture.
• Experience deploying LLM systems into production at enterprise scale.
• Experience with large-scale data and knowledge-retrieval systems.
• Experience creating measurable AI evaluation frameworks.
• Experience with model monitoring, observability, and production reliability.
• Strong communication and stakeholder-management skills.
• Experience mentoring Data Scientists and ML Engineers.

Work Arrangement

• First 6 months: Remote
• After 6 months: Onsite in Raleigh, NC
• Candidates must be willing to relocate to Raleigh, NC after the initial remote period.