Overview
Remote
$60 - $70
Contract - W2
Skills
Artificial Intelligence
Natural Language Processing
Llama
Vector Databases
Vertex
Machine Learning (ML)
Python
Orchestration
Job Details
Key Responsibilities:
- Design, develop, and optimize LLaMA-based and other open-source LLM solutions.
- Fine-tune models for domain-specific applications using PyTorch, Transformers, or Hugging Face ecosystems.
- Build and deploy scalable LLM pipelines integrating retrieval-augmented generation (RAG), vector databases, and prompt orchestration tools.
- Evaluate and benchmark model performance, accuracy, latency, and cost efficiency.
- Collaborate with data scientists and ML engineers to prepare and clean large text datasets.
- Implement responsible AI principles ensuring fairness, transparency, and compliance.
Required Skills & Experience:
- Proven experience working with Meta s LLaMA models (LLaMA 2 / 3 / Llama Talent platform).
- Strong programming in Python, with frameworks like PyTorch, LangChain, and Hugging Face Transformers.
- Deep understanding of LLM architecture, tokenization, embeddings, and fine-tuning techniques.
- Experience deploying models via REST APIs, Docker, or Kubernetes in production environments.
- Familiarity with vector databases (e.g., FAISS, Pinecone, Milvus) and prompt pipelines.
- Solid knowledge of MLOps tools (Weights & Biases, MLflow, or Vertex AI).
Preferred Qualifications:
- Experience with RAG-based or agentic AI systems (LangGraph, CrewAI, etc.)
- Background in NLP research or AI model evaluation.
- Understanding of Meta AI ecosystem tools and deployment practices.
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.