- Location
- San Francisco, California, United States
- Employment
- Full time
- Level
- Mid level
- Posted
- 25 November
About this role
About Reducto
Reducto is the agentic document platform for leading AI teams who demand enterprise performance at scale. We provide a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows.
We’ve grown rapidly, increasing revenue 8x year over year and partnering with hundreds of companies, from leading AI teams like Harvey, Vanta, and Scale, to enterprise customers across FAANG and top trading firms.
Reducto has raised over $100M from world-class investors including a16z, Benchmark, and First Round Capital.
We would love to meet you if you:
Philosophy: You are your own worst critic. You have a high bar for quality and don’t rest until the job is done right - no settling for 90%. We want someone who ships fast, with high agency, and who doesn't just voice problems but actively jumps in to fix them.
Experience: You have 2+ years of experience with training, fine tuning, and evaluating ML models used in production systems
Language/Skills: You’re exceptional at Python or similar, and are well versed with both traditional computer vision and VLMs
Tools: Build your own tools as needed - like a quick Streamlit app to test hypotheses or create a dataset.
Approach: A quantitative approach to building products. Ability to debug, experiment, and iterate fast. You should be comfortable getting hands-on with the full development lifecycle, from ideation to shipping to users.
The core work will include:
Training and deploying new state of the art models for parsing and interpreting unstructured data
Experimenting with novel techniques to improve LLM accuracy
Build data pipelines, evaluate model performance, and integrate models into the product
Working directly with the founders and customers to shape the product direction and engineering strategy
Bonus points if you:
Have prior experience founding a company or building products at early stages
Are ambitious and driven, and care a lot about doing great work with great people
Keep up with the latest developments in ML/AI
This is an in person role at our office in SF. We’re an early stage company which means that the role requires working hard and moving quickly. Please only apply if that excites you.
About Reducto
Nearly 80% of enterprise data is in unstructured formats like PDFs
PDFs are the status quo for enterprise knowledge in nearly every industry. Insurance claims, financial statements, invoices, and health records are all stored in a structure that’s simply impractical for use in digital workflows. This isn’t an inconvenience - it’s a critical bottleneck that leads to dozens of wasted hours every week.
Traditional approaches fail at reliably extracting information in complex PDFs
OCR and even more sophisticated ML approaches work for simple text documents but are unreliable for anything more complex. Text from different columns are jumbled together, figures are ignored, and tables are a nightmare to get right. Overcoming this usually requires a large engineering effort dedicated to building specialized pipelines for every document type you work with.
Reducto breaks document layouts into subsections and then contextually parses each depending on the type of content. This is made possible by a combination of vision models, LLMs, and a suite of heuristics we built over time. Put simply, we can help you:
Accurately extract text and tables even with nonstandard layouts
Automatically convert graphs to tabular data and summarize images in documents
Extract important fields from complex forms with simple, natural language instructions
Build powerful retrieval pipelines using Reducto’s document metadata
Intelligently chunk information using the document’s layout data
Benefits at Reducto
At Reducto, we’re invested in the well-being and growth of our team. Here’s what we currently offer:
Unlimited PTO: We believe great work requires recharging.
Lunch: Receive a free lunch to eat with your teammates daily at the office
Reimbursed Transportation: Provide us with your receipts and we’ll take care of the costs
Insurance: Generous health insurance covering medical, dental, and vision.
Health and Wellness Budget: We provide up to $150/mo reimbursement for health and wellness spending, such as gym memberships, fitness classes, or similar.
Parental Leave: Work with us to build a leave schedule that works for you and your family
Reducto is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law.
As published by Reducto. Applications are handled on their site.
Skills this posting mentions
About Reducto
Reducto is the complete agentic document platform for leading AI teams needing performance at enterprise scale. We provide a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows. We currently power the best AI teams ranging from startups to Fortune 10 companies across all industries: legal, finance, healthcare, and more. We are built for enterprise workloads with flexible deployment options from the cloud to fully air-gapped environments, SOC II and HIPAA compliance, and zero data retention.
All 35 openings at ReductoOne click, then it is written
Apply to Reducto with a resume written for this role.
Queue Machine Learning Engineer and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Reducto’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- 25 sent a week, free
- No card
- Nothing sent until you say so
More roles at Reducto
See all- 5 October
- 21 September
- 21 September
- 14 September
- 10 September
- 8 September
Similar roles elsewhere
See more- 31 October
Software Engineer (Machine Learning) Intern (Summer 2027)
AffirmSan Francisco, California
InternshipData and ML - 31 October
Software Engineer, Machine Learning Platform - Gen AI
DoorDashSan Francisco, CA +2
CA$120k - CA$150k/yrData and ML - 30 October
- 30 October
- 30 October
Put this to work
Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
Free, no card. Up to 25 applications sent a week, and nothing is sent until you say so.
Listed from the job board Reducto publishes. Refolk is not the employer and does not handle their hiring. Applications go to Reducto directly.
Hiring at Reducto? Post this role to the Refolk talent pool for $299, once. No commission, refunded if I find nobody. Post a role for $299