LLM Engineer - Remote 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: LLM Engineer Location: 100% Remote (U.S.) Position Type: Full-time, Direct W2 Salary Range: $100,000–$150,000 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. Job Summary: We are looking for an LLM 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.
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
Ten 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 venkat.r@bvteck.com or contact us at (908) 505-3899. Learn more about Bright Vision Technologies at www.bvteck.com Bright Vision Technologies is an Equal Opportunity Employer. Equal Employment Opportunity (EEO) Statement 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. Powered by JazzHR A3Y8Dh8vRl