Machine Learning Engineer

Join to apply for the Machine Learning Engineer role at Enormous Enterprise LLC

Company: Enormous Enterprise LLC

Location: Alpharetta, GA 30009

Remote Role: Remote (Alpharetta, GA)

Employment Type: Full-time (W2 candidates with minimum validity of 12 months)

Posted: January 05, 2026

Salary: DOE

We’re working on an AI evidence engine focused on LLM. 2 rounds of Zoom interview then offer.

• Develop, fine‑tune, and optimize LLMs and modern deep learning models.
• Write high‑quality prompts, instructions, and training examples to shape model behavior.
• Design, implement, and maintain instruction orchestration and evaluation workflows for LLM‑based systems.
• Build and maintain training pipelines, datasets, and evaluation workflows.
• Design and execute functional and automated tests to validate AI outputs and system behavior.
• Analyze model performance, identify failure patterns (e.g., accuracy gaps, hallucinations, edge cases), and drive improvements.
• Collaborate with engineering and product teams (and review partner or vendor work) to deploy and iterate on AI features.
• Contribute to the ongoing maintenance and improvement of existing AI systems.

• 7+ years of experience in machine learning, NLP, or deep learning.
• 4+ years of experience with machine learning, NLP, or deep learning projects.
• Hands‑on experience with LLMs (GPT, LLaMA, Mistral, or similar) in applied or production contexts.
• Strong Python skills with PyTorch or Tensor Flow.
• Familiarity with Hugging Face tools and modern model‑training workflows.
• Experience evaluating AI output quality, hallucination behavior, reliability, and consistency.
• Experience designing automated evaluation, regression testing, or benchmarking pipelines for AI systems.
• Experience optimizing LLM and deep learning workloads on AWS, including model training, GPU utilization, and cost‑efficient inference deployments.
• Strong communication skills for writing prompts, instructions, technical documentation, and evaluation artifacts.
• Ability to work with minimal direction, take ownership of problem areas, and operate effectively in ambiguous problem spaces.
• Good clinical and claims knowledge required.
• Healthcare data experience required, including working knowledge of relevant protocols.