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Machine Learning Researcher, Document Understanding

Brighterway

San Francisco, CAFull-timePosted 1 day agoStill listed today

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At a glance

Compensation
No compensation found
Location
San Francisco, CA
Schedule
Full-time
Work Authorization
Not specified

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Job overview

Brighterway is building claims software on an AI-native document-processing foundation. The Machine Learning Researcher will advance document understanding for large medical and legal files, including sorting, summarization, duplicate detection, OCR, and quality evaluation. The role combines experimentation with production implementation, working closely with engineering and using customer feedback to measure quality and improve multi-step pipelines.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningNatural Language ProcessingLarge Language ModelsPromptingFine-TuningRetrievalEvaluationPythonReproducible ExperimentationDocument AIOCRLayout AnalysisHealthcare NLPLegal NLP

Qualifications

Graduate Degree or Equivalent Research ExperienceStrong Applied ML RecordPublications or Open-Source Work

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
Paid Time Off

Full job description

About Brighterway Brighterway builds AI-native claims software and administration for casualty claims. We started in workers' compensation medical-legal review, where our agentic document pipeline sorts, de-duplicates and summarizes some of the most document-heavy files in the industry for national medical-evaluation networks. We are now building the claims platform on top of that foundation: intake across mail, fax, phone and email, bill review, subrogation, reserving signals, a workflow language, and state and federal reporting. We are backed by Y Combinator and Maverick Ventures. Our customers handle protected health information every day, so we run HIPAA, SOC 2 and ISO 27001 programs. The team is small and technical and sits close to customers. Everyone ships, and everyone talks to the people who use what they ship. The role Our product is only as good as our ability to read a 3,000-page medical file and come out with the right chronology, the right duplicates removed, and the right facts surfaced. You will push the frontier of that capability: agentic document splitting and sorting, long-context summarization, duplicate and near-duplicate detection, OCR on hostile scans, and evaluation methods that tell us when quality drifts before customers do. What you will do

  • Design and run experiments on LLM-based pipelines for classification, extraction, summarization and reasoning over medical and legal documents.

  • Build evaluation sets and metrics from real customer feedback, and make quality measurable release to release.

  • Improve cost, latency and reliability of multi-step agentic pipelines without giving up accuracy.

  • Work with engineering to move research results into production quickly.

  • Follow model releases and decide when a new model or technique is worth adopting.

What we look for

  • Graduate degree or equivalent research experience in machine learning or NLP, or a strong record of applied ML work.

  • Hands-on experience with large language models: prompting, fine-tuning, retrieval, evaluation.

  • Strong Python and the discipline to make experiments reproducible.

  • Comfort with messy real-world data and imperfect ground truth.

Nice to have

  • Document AI, OCR or layout analysis experience.

  • Healthcare or legal NLP experience.

  • Publications or open-source work in the area.

How we work

  • Small team, high trust, direct access to founders and customers.

  • We ship to production weekly and measure ourselves on customer outcomes.

  • Competitive salary and meaningful equity. Health, dental and vision coverage. Flexible time off.

Brighterway is an equal opportunity employer. Location: San Francisco, CA (in person, Financial District office) Employment type: Full-time

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