AI Engineer / Data Scientist – Generative AI & LLM Specialist

Overview

Remote
65 - 70
Accepts corp to corp applications
Contract - W2
Contract - 6 Month(s)
10% Travel
Able to Provide Sponsorship

Skills

Generative AI Large Language Models (LLMs) Fine-tuning (LoRA
QLoRA
GPT-4o
LLaMA-3) RAG (Retrieval-Augmented Generation) & GraphRAG Agentic / Autonomous AI Systems Prompt Engineering
Python PyTorch TensorFlow Hugging Face Transformers Scikit-Learn MLflow AutoGen
LangChain
LlamaIndex
Pandas
NumPy PySpark / Spark / Databricks SQL
NoSQL
Snowflake Data pipelines
ETL
Real-time analytics
ableau
Power BI
Plotly
Matplotlib
Agile/Scrum Product & Stakeholder Management Team mentoring and knowledge sharing
Generative Artificial Intelligence (AI)
Artificial Intelligence
Conflict Resolution
Data Processing
Large Language Models (LLMs)
Machine Learning Operations (ML Ops)

Job Details

AI Engineer / Data Scientist – Generative AI & LLM Specialist

We are seeking a skilled Data Scientist / AI Engineer with expertise in Generative AI, Large Language Models (LLMs), and RAG systems. The ideal candidate will design, fine-tune, and deploy language models, optimize data pipelines, and implement AI solutions that drive business impact.

Key Responsibilities:

  • Prepare and process datasets for language model training and fine-tuning.

  • Fine-tune LLMs using frameworks such as LoRA, QLoRA, GPT-4o, LLaMA-3.

  • Develop and deploy RAG pipelines for real-time knowledge retrieval.

  • Benchmark model performance, analyze results, and optimize models for production.

  • Collaborate with cross-functional teams to deliver scalable AI and data solutions.

  • Stay up-to-date with the latest AI/ML research and emerging technologies.

Requirements:

  • Proven experience with LLMs, Generative AI, and fine-tuning models with proprietary datasets.

  • Strong programming skills in Python and experience with PyTorch, TensorFlow, or Hugging Face Transformers.

  • Familiarity with data processing libraries such as Pandas, NumPy, and PySpark.

  • Experience with vector and graph databases (Pinecone, Faiss, ChromaDB, Neo4j).

  • Knowledge of cloud platforms: AWS, Azure, Google Cloud Platform and MLOps practices (CI/CD, MLflow, Docker).

  • Excellent problem-solving and collaboration skills.

Preferred:

  • Experience with Autonomous AI, agentic AI systems, and reasoning models.

  • Knowledge of RAG, GraphRAG frameworks, and enterprise-scale AI deployments.

  • Advanced degree in Data Science, Computer Science, or related field.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.