Remote LLM Engineer: Fine-Tune & Scale Transformers

Bright-Vision-Technologies; United States; Remote; USD 72,000 - 100,000; Full time

Job summary

Bright Vision Technologies is seeking an LLM Engineer to design and operate fine-tuning pipelines for large language models, spanning supervised, RLHF, and preference-based approaches. This remote role requires strong ML background and production-grade engineering discipline.

You will collaborate with product, design, and operations teams across the US, tackle data quality, compute budgets, and shipping velocity while mentoring junior engineers.

Qualifications

• Master’s or PhD in Computer Science, ML, or related field, or equivalent experience.
• Six or more years of ML research and engineering experience with LLM exposure.
• Strong Python and PyTorch proficiency.
• Hands-on fine-tuning of transformer-based language models at scale.
• Familiarity with distributed training strategies (FSDP, ZeRO, pipeline parallelism).
• Experience with RLHF, DPO, or other preference optimization techniques.
• Strong evaluation methodology, benchmarks, and human evaluation design.

Responsibilities

• Design, execute, and operationalize fine-tuning workflows for LLMs across supervision, RLHF, and preference-based approaches.
• Collaborate with product, design, engineering, operations, and business stakeholders to translate requirements into solutions.
• Maintain production-grade training pipelines with reliability and scalability.
• Mentor junior engineers and participate in code and design reviews.

Skills

Python

PyTorch

Distributed training

RLHF/DPO

Evaluation design

GPU training

Communication

Production-grade engineering

Education

Master’s or PhD in Computer Science / ML

Tools

FSDP

ZeRO

Pipeline parallelism

Job description

Bright Vision Technologies is seeking an LLM Engineer to design and operate fine-tuning pipelines for large language models, spanning supervised, RLHF, and preference-based approaches. This remote role requires strong ML background and production-grade engineering discipline.

You will collaborate with product, design, and operations teams across the US, tackle data quality, compute budgets, and shipping velocity while mentoring junior engineers.