LLM Fine-Tuning Engineer

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications.

As we continue to grow, we’re looking for a skilled LLM Fine-Tuning Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology.

This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

LLM Fine-Tuning Engineer

Job Title: LLM Fine-Tuning Engineer

Location: 100% Remote (Continental United States)

Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)

Experience: 6+ years

Salary Range : $100k to $150k per annnum

Sponsorship: No new H1B sponsorship available. H1B transfers welcomed for qualified candidates.

Employment Type: Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party)

Engagement: Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap

Compensation: Competitive base salary commensurate with experience, plus benefits.

Employment Terms & Visa Policy

This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies.

This role is part of Bright Vision Technologies’ in-house Statement of Work (SOW) engagement. The client, end customer, and employer for this position is Bright Vision Technologies — there is no third-party client, vendor, or implementation partner involved.

We do not engage in C2C, 1099, or third-party arrangements for this role.

BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING PLEASE.

Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables.

No new H1B sponsorship is available for this role.

However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates.

For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience.

Job Summary

We are looking for an LLM Fine-Tuning 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.

Key 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

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

Required 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

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

How To Apply

Would you like to know more about this opportunity?

For immediate consideration, please send your resume to jaya@bvteck.com or contact us at (908) 505-3545. Learn more about Bright Vision Technologies at www.bvteck.com.

Position offered by “No Fee Agency.”

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.

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