Bright Vision Technologies is a software development company that creates innovative solutions for automating and optimizing business operations. They are seeking an LLM Fine-Tuning Engineer to join their team and contribute to their mission of transforming business processes through technology.
Requirements
- Design and execute fine-tuning experiments for large language models using supervised, DPO, RLHF, and related techniques.
- Lead dataset construction, curation, and quality assurance processes for instruction tuning and preference data.
- Build scalable training pipelines on top of modern distributed training frameworks.
- Tune hyperparameters, optimizer configurations, and training stability strategies for large-model fine-tuning.
- Implement parameter-efficient fine-tuning techniques such as LoRA, QLoRA, and adapter-based methods.
- Design rigorous evaluation suites including automated benchmarks, human evaluation, and capability-specific probes.
- Implement safety, refusal, and policy evaluations to track model behavior across releases.
- Operate large-scale training jobs on GPU clusters, diagnosing failures and recovering training state reliably.
- Optimize training throughput using mixed precision, sequence packing, and efficient attention implementations.
- Manage model artifacts, lineage tracking, and reproducibility across many concurrent experiments.
- Collaborate with product, research, and platform teams to align fine-tuning roadmaps with business needs.
- Document training methodology, results, and decisions clearly for technical and non-technical audiences.
- Mentor engineers on fine-tuning best practices, evaluation rigor, and responsible deployment.
- Stay current with LLM research and translate advances into production-ready fine-tuning recipes.
Benefits
- Competitive base salary commensurate with experience
- Plus benefits
