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AI Research Engineer; Applied AI

Remote / Online - Candidates ideally in
Bellevue, King County, Washington, 98009, USA
Listing for: Bright Vision Technologies
Full Time, Remote/Work from Home position
Listed on 2026-05-21
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 120000 - 150000 USD Yearly USD 120000.00 150000.00 YEAR
Job Description & How to Apply Below
Position: AI Research Engineer (Applied AI)

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 AI Research Engineer (Applied AI) 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.

AI Research Engineer (Applied AI)

Job Title: AI Research Engineer (Applied AI)

Location: 100% Remote (Continental United States)

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

Experience: 6+ years

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 seeking an AI Research Engineer to bridge cutting-edge applied research and production engineering, designing and shipping advanced machine learning systems that solve high-impact business problems. The role blends scientific rigor with practical software engineering, requiring deep understanding of modern ML and deep learning techniques alongside the ability to build robust, scalable, and well-instrumented production pipelines. The ideal candidate stays current with the rapidly evolving AI research landscape, can critically evaluate new techniques for real-world applicability, and is comfortable operating across the full lifecycle from problem framing and experimentation to deployment and continuous improvement.

Key Responsibilities
  • Design, prototype, and evaluate applied AI solutions across natural language, vision, recommendation, and structured data domains.
  • Translate ambiguous business problems into well-scoped ML formulations with clear success metrics and evaluation strategies.
  • Stay current with the latest research in deep learning, large language models, and adjacent areas, and assess applicability to internal use cases.
  • Implement rigorous experimentation workflows including baselines, ablations, and statistically sound evaluation methodology.
  • Build production-quality training and inference pipelines using modern ML frameworks and orchestration tools.
  • Collaborate with ML platform engineers to ensure efficient use of compute, storage, and accelerator resources.
  • Optimize models for accuracy, latency, throughput, and cost based on production requirements.
  • Develop tooling for dataset construction, labeling, validation, and ongoing monitoring of data quality.
  • Partner with product, design, and domain experts to ensure model behavior aligns with user needs and policy requirements.
  • Implement safety, fairness, and reliability evaluations and incorporate…
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