Senior AI Applications Engineer - LLM Fine-Tuning (Remote)

Bright Vision Technologies; Tampa (FL); Remote; USD 100,000 - 175,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Applications Engineer to design, execute, and operationalize fine-tuning workflows for large language models across supervised, preference-based, and reinforcement learning approaches. The role requires deep practical experience with modern training stacks, careful dataset construction, rigorous evaluation, and production-grade engineering practices.

You will mentor engineers and collaborate across product, design, and operations to ship robust

Qualifications

• Master’s or PhD in Computer Science, Machine Learning, or a related field; or equivalent experience.
• Six or more years of combined ML research and engineering experience, with significant LLM exposure.
• Strong proficiency in Python and modern deep learning frameworks, especially PyTorch.
• Hands-on experience fine-tuning transformer-based language models at non-trivial scale.
• Familiarity with distributed training strategies including FSDP, ZeRO, and pipeline parallelism.
• Experience with RLHF, DPO, or other preference optimization techniques.
• Strong understanding of evaluation methodology, benchmarks, and human evaluation design.
• Experience operating training jobs on GPU clusters and recovering from failures.
• Strong written and verbal communication skills.
• Track record of shipping or publishing impactful LLM work.

Responsibilities

• Design and execute fine-tuning experiments for LLMs using supervised, DPO, RLHF.
• Lead dataset construction and quality assurance processes for instruction tuning and preference data.
• Build scalable training pipelines on modern distributed frameworks.
• Tune hyperparameters and training stability for large-model fine-tuning.
• Implement parameter-efficient fine-tuning techniques such as LoRA, QLoRA, and adapters.
• 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.

Skills

Python

PyTorch

LLMs

Distributed training

RLHF/DPO

Evaluation design

Communication

GPU clusters

Education

Master’s or PhD in CS/ML

Job description

Bright Vision Technologies is seeking an AI Applications Engineer to design, execute, and operationalize fine-tuning workflows for large language models across supervised, preference-based, and reinforcement learning approaches. The role requires deep practical experience with modern training stacks, careful dataset construction, rigorous evaluation, and production-grade engineering practices.

You will mentor engineers and collaborate across product, design, and operations to ship robust