Senior LLM Fine-Tuning Engineer — Remote

Bright Vision Technologies; Sugar Land (TX); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies seeks a Large Language Model Specialist to design, implement, and operate fine-tuning workflows for large language models in production. You will build scalable training pipelines and collaborate with product, design, engineering, and operations teams to translate complex requirements into robust, production-ready solutions.

This remote role rewards practical ML intuition, strong production engineering skills, and meticulous evaluation.

Qualifications

• Master’s or PhD in Computer Science, ML, or a related field; or equivalent experience.
• Six or more years of ML research and engineering experience with LLMs.
• Strong proficiency in Python and PyTorch.
• Experience fine-tuning transformer-based LLMs at scale.
• Familiarity with distributed training strategies (FSDP, ZeRO, pipeline parallelism).
• Strong written and verbal communication skills.

Responsibilities

• 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.
• Operate large-scale training jobs on GPU clusters, diagnosing failures and recovering training state reliably.

Skills

Python

LLM fine-tuning

Distributed training

RLHF

Evaluation design

Mentorship

Education

Master’s or PhD in CS/ML

Tools

PyTorch

Job description

Bright Vision Technologies seeks a Large Language Model Specialist to design, implement, and operate fine-tuning workflows for large language models in production. You will build scalable training pipelines and collaborate with product, design, engineering, and operations teams to translate complex requirements into robust, production-ready solutions.

This remote role rewards practical ML intuition, strong production engineering skills, and meticulous evaluation.