Machine Learning Researcher, Document Understanding

Brighterway, Inc.; San Francisco (CA); On-site; USD 130,000 - 180,000; Full time

Benefits offered by this job

Health, dental and vision coverage

Competitive equity package

Flexible time off

Job summary

Brighterway, a San Francisco-based AI-native claims platform, seeks a machine learning/NLP researcher to advance agentic document processing. You will design LLM-based pipelines for classification, extraction, and summarization on complex medical-legal files while measuring quality with robust evaluation sets.

You will collaborate with engineering to push research into production, improve cost and latency, and stay current with model releases.

Qualifications

• Graduate degree or equivalent research experience in ML/NLP.
• Hands-on experience with large language models, prompting and fine-tuning.
• Strong Python and the discipline to make experiments reproducible.
• Comfort with messy real-world data and imperfect ground truth.

Responsibilities

• 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.

Skills

ML/NLP degree/experience

LLMs experience

Python

Experiment reproducibility

Education

Graduate degree in ML/NLP

Tools

OCR

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