AI Engineer - Model Adaptation & Evaluation
Core
Adapt, evaluate, and deploy open-weight language models for specialized operational use cases in constrained or secure environments.
Role type
LLM Fine-Tuning Engineer
Builds
Task-specific systems derived from foundation models
Domain
Artificial Intelligence / Large Language Models
Deliverable
production ML models
Required skills
supervised fine-tuning (SFT), parameter-efficient fine-tuning (LoRA, QLoRA), preference tuning (DPO), dataset curation, synthetic data generation, PyTorch, Hugging Face Transformers, GPU optimization, quantization-aware workflows
Preferred skills
debugging model regressions, translating domain needs into evaluation criteria
Technologies
PyTorch, Hugging Face Transformers
Responsibilities
Fine-tune and adapt open-weight LLMs for specialized use cases; Design, run, and compare post-training approaches; Build, clean, and improve high-quality datasets; Generate and validate synthetic data; Define and implement evaluation methods; Analyze model regressions and failure modes; Package, serve, and operationalize tuned models in restricted environments
Seniority
Mid-to-Senior, hands-on IC