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Bright Vision Technologies

AI-powered talent intelligence and automation platform

Foundation Model Engineer

Full-TimePosted on 9/28/2026
$200k - $230k/yr
Expert
Remote in USA
Remote
No H1B Sponsorship

About the job

Requirements
  • At least 10 years of combined machine-learning research and engineering experience, including significant large-language-model 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 Fully Sharded Data Parallel, ZeRO, and pipeline parallelism.
  • Experience with reinforcement learning from human feedback, direct preference optimization, 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.
  • A track record of shipping or publishing impactful large-language-model work.
Responsibilities
  • Design, execute, and operationalize fine-tuning workflows for large language models using supervised, preference-based, and reinforcement-learning approaches.
  • Construct datasets and establish rigorous evaluation methodology for model training and deployment.
  • Operate complex training pipelines reliably on GPU clusters, including recovery from failures.
  • Translate ambiguous requirements from product, design, engineering, operations, and business stakeholders into well-engineered solutions.
  • Conduct code reviews and design reviews.
  • Mentor more junior engineers.
Desired Qualifications
  • Publications at top-tier machine-learning venues.
  • Experience with multimodal model fine-tuning.
  • Familiarity with synthetic-data generation and dataset distillation.
  • Open-source contributions to large-language-model training libraries.
  • Exposure to responsible-AI evaluation and red-teaming practices.

About the company

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Bright Vision Technologies

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Bright Vision Technologies offers Lumina, an AI-powered platform for talent intelligence and enterprise automation, along with consulting and staffing services. Lumina analyzes unstructured data with generative AI, Large Language Models orchestrated via LangChain, and Retrieval-Augmented Generation to support sourcing and screening candidates, integrated with CRM, ERP, and HRMS on a cloud-native microservices architecture across AWS, Azure, and Google Cloud. The company differentiates itself by combining a sophisticated AI product with hands-on consulting and staffing expertise, plus its minority-owned status and a dual model that helps clients implement technology and solve broader business challenges. Its goal is to streamline and automate complex workflows in IT talent acquisition and management to enable digital transformation and efficient enterprise operations.

Company Size

51-200

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

2020

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Simplify Jobs

Simplify's Take

What believers are saying

  • April 2026 LinkedIn launch signals active product commercialization and go-to-market acceleration.
  • August 2026 site updates show hiring across Bridgewater, Princeton, and Chennai.
  • The company’s minority-owned status and U.S.-India footprint strengthen enterprise procurement positioning.

What critics are saying

  • No disclosed funding, customers, or revenue makes Lumina's traction impossible to verify.
  • The June 2026 pivot from staffing to product risks channel conflict and execution drag.
  • Enterprise AI recruiting faces entrenched rivals like Workday, LinkedIn, and Eightfold by 2027.

What makes Bright Vision Technologies unique

  • April 2026 launch of Lumina combines talent intelligence, automation, and hybrid cloud.
  • Lumina integrates RAG, LLM orchestration, semantic matching, and blockchain credential verification.
  • Bright Vision serves staffing and consulting clients, enabling implementation alongside the product.

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Benefits

Remote Work Options

INACTIVE