Foundation Model Engineer

Bright Vision Technologies; Leander (TX); Remote; USD 200,000 - 230,000; Full time

Job summary

Bright Vision Technologies is seeking a Foundation Model Engineer to design, execute, and operationalize fine-tuning workflows for large language models across supervised, preference-based, and reinforcement learning approaches. The role emphasizes practical ML experience, production-grade engineering, and collaboration with product, design, and operations teams.

The candidate should have deep experience with modern training stacks, robust evaluation methods, and a track record of shipping

Qualifications

• 10+ years in ML research and engineering with significant LLM exposure.
• Strong proficiency in Python and PyTorch.
• Hands-on experience fine-tuning transformer-based language models at non-trivial scale.

Responsibilities

• Design, execute, and operationalize fine-tuning workflows for large language models across supervised, preference-based, and RL approaches.
• Collaborate with cross-functional teams to translate ambiguous requirements into well-engineered solutions.
• Maintain production-grade training pipelines and ensure reliability in distributed environments.

Skills

Python

PyTorch

LLM fine-tuning

Distributed training

RLHF / DPO

Evaluation methodology

Tools

FSDP

ZeRO

Pipeline parallelism

Job description

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title

Foundation ModelEngineer

Location

100% Remote (U.S.)

Position Type

Full-time, Direct W2

Salary Range

$200,000–$230,000 Annually

Experience Required

10+ years

Sponsorship

U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.

Bright Vision Technologies is an Equal Opportunity Employer

Job Summary

We are looking for an Foundation Model 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 methodology, and the engineering discipline to operate complex training pipelines reliably. The ideal candidate combines strong ML intuition with production-grade engineering practices, and is comfortable navigating the trade-offs between data quality, compute budget, evaluation rigor, and shipping velocity. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production.

Required Qualifications

• 10 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.

Preferred Qualifications

• Publications at top-tier ML venues.
• Experience with multimodal model fine-tuning.
• Familiarity with synthetic data generation and dataset distillation.
• Open-source contributions to LLM training libraries.
• Exposure to responsible AI evaluation and red-teaming practices.

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.