AI Applications Engineer

Bright Vision Technologies

Reston (VA)

On-site

USD 100,000 - 175,000

Full time

9 days ago

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Job summary

Bright Vision Technologies is seeking an AI Applications Engineer for a 100% remote role in the United States. The position focuses on designing, executing, and operationalizing fine-tuning workflows for large language models across supervised, reinforcement learning, and preference-based approaches.

The ideal candidate has 6+ years of ML research and engineering experience, deep Python and PyTorch skills, and hands-on transformer LLM fine-tuning on GPU clusters.

Qualifications

  • Master’s or PhD in Computer Science, ML, or 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 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, execute, and operationalize fine-tuning workflows for large language models across supervised, preference-based, and reinforcement learning approaches.
  • Collaborate with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions.
  • Raise the bar through code review, design review, and mentorship of more junior engineers.
  • Maintain production-grade training pipelines with rigorous evaluation and robust tooling.

Skills

Python
PyTorch
LLM fine-tuning
Distributed training
RLHF/DPO
Evaluation design
Production-grade engineering
Communication skills
Shipping LLM work

Education

Master’s or PhD in Computer Science or ML
Equivalent experience

Tools

GPU clusters
FSDP
ZeRO
Pipeline parallelism

Job description

AI Applications 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: AI Applications Engineer

Location: 100% Remote (United States)

Position Type: Full-time, Direct W2

Salary Range: $100,000–$175,000 Annually

Experience: 6+ years

Sponsorship: U.S. Citizens, Green CardHolders, EADHolders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.

We are looking for 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 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
  • 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.
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.

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