---
title: 'Machine Learning Infra Engineer at Reducto'
canonical: 'https://feeny.ai/job/machine-learning-infra-engineer-reducto-san-francisco-mkgg38w9rzmb'
type: 'job'
last_seen: '2026-09-07'
---

# Machine Learning Infra Engineer at Reducto

- **Company:** Reducto
- **Location:** San Francisco, CA
- **Compensation:** $200k–$300k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-05-13
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.ashbyhq.com/reducto/df35cc55-1783-402d-b0d9-ca1352f50d0b

## Job description

## 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.

## THE OPPORTUNITY

As an ML Infra Engineer, you’ll play a key role in building the inference and training frameworks that make it possible to deliver results at scale. You’ll collaborate closely with our ML and Platform teams to scale training across nodes, develop faster and more efficient serving, and create observability across the stack. This is a high-impact role where you’ll help define what high performance ML training and inference look like at Reducto.

## WHAT YOU’LL DO

- Build, and maintain our training and inference stack with an emphasis for fast iteration on training + flexibility for exploring new methods and high performance in inference.
- Develop benchmarks for both sets of stacks to identify bottlenecks.
- Explore SOTA advances in training and inference and work to apply them.
- Design systems for scaling model training across multi-node, multi-GPU environments with strong reliability and observability.
- Scale distributed training and inference workloads across large GPU clusters while improving utilization, reliability, and cost efficiency.
- Build the tooling, abstractions, and observability that help ML engineers move faster from experiment to production.

## YOU’LL THRIVE HERE IF YOU:

- Hold yourself to a high bar for quality and precision.
- Enjoy solving complex problems and building from first principles.
- Have strong Python skills + a background in systems engineering.
- Are comfortable with Kubernetes and distributed training frameworks.
- Love getting your hands dirty with real-world implementation challenges.
- Operate well in fast-changing, high-growth environments.
- Collaborate effectively across technical and non-technical teams.
- Take full ownership from strategy through execution.
- Have 3+ years of experience.

## BONUS POINTS IF YOU:

- Have experience at an early-stage or high-growth startup.
- Have developed in open source training/inference stacks in a meaningful way.
- Are excited to set up distributed inference across 100s-1000s of GPUs.
- Care deeply about combining technical excellence with business impact.

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.

## MORE 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 https://www.reducto.ai/blog/the-real-cost-of-manual-document-processing.

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 https://www.reducto.ai/ 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.

## About Reducto

## Company Overview
- **One-liner**: Reducto is the agentic document platform for leading AI teams, providing a comprehensive toolkit for document parsing, extraction, and automation at enterprise scale.
- **Entity Type**: Private (Series B)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2023
- **Founders**: Adit Abraham (CEO) and Raunak Chowdhuri (CTO)

## Core Business
- **Primary industry**: Document AI / Enterprise Software / Artificial Intelligence
- **Target customers**: AI teams and enterprises across legal, finance, healthcare, and insurance sectors — ranging from startups to Fortune 10 companies.
- **Mission or purpose**: To unlock messy, real-world document data so that leading AI teams can build smarter systems, faster decisions, and better products.

## Products & Services
- **Parse**: Reads documents like a human would, capturing layout, structure, and meaning with high accuracy. Uses Agentic OCR that reviews and corrects outputs in real-time for near-perfect results.
- **Extract**: Extracts structured data directly from documents with schema-level precision — invoice fields, onboarding forms, financial disclosures, and more.
- **Edit**: Dynamically fills in detected blanks, tables, and checkboxes with supplied data across scanned PDFs, digital forms, and complex multi-page documents — no bounding boxes or templates required.
- **Split**: Automatically separates multi-document files or long forms into individually useful units using intelligent, layout-aware heuristics.
- **Deep Extract**: The most accurate structured document extraction agent yet, leveraging vision-language models for context-aware extraction.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Total Funding**: $108.4M across four rounds
  - Pre-Seed (Apr 2024): $500K led by Y Combinator
  - Seed (Oct 2024): $8.4M led by First Round Capital
  - Series A (Apr 2025): $24.5M led by Benchmark
  - Series B (Nov 2025): $75M led by Andreessen Horowitz
- **Notable Investors**: Benchmark, First Round Capital, Andreessen Horowitz, Box Group, Y Combinator, and founders of Dropbox and Airtable.
- **Growth Signals**: Headcount grew 313.3% YoY to 43 employees; trusted by leading AI teams including Harvey, Scale AI, and Vanta; serves Fortune 10 enterprises; operates in 6 countries.

## Competitive Advantages
- **Agentic OCR**: Combines custom in-house vision models with leading frontier VLMs that review and correct outputs in real-time, achieving near-perfect accuracy even on edge cases.
- **Enterprise-grade security**: SOC 2 and HIPAA compliant, with flexible deployment options from cloud to fully air-gapped environments and zero data retention.
- **Battle-tested infrastructure**: 99.9%+ uptime, built for enterprise workloads at scale.
- **Deep technical moat**: Founders are MIT CS graduates with published computer vision research and experience at Google and MIT Media Lab.

## Strategic Focus
- Scaling the platform to serve more enterprise customers across legal, finance, healthcare, and insurance verticals.
- Continuing to advance proprietary vision-language models for document understanding.
- Expanding the team, particularly in engineering, machine learning, and go-to-market roles.

## Why Work Here
- **Culture**: "We stay small on purpose, so ideas move fast, ownership runs deep, and your work directly shapes the future of the company." The team is described as builders — curious, humble, and relentless about solving real problems.
- **Team**: 43 employees with strong talent from MIT, Stanford, and companies like Scale AI, Vanta, Meta, and Hudson River Trading. Technical roles make up 27% of the team.
- **Location**: San Francisco office with daily lunch, snacks, and commute stipends.
- **Benefits**: High-quality medical, dental, and vision coverage; 401k with 4% company match; health and wellness stipends (gym, fitness classes); parental leave; flexible PTO.
- **Open roles**: 35 active job postings across engineering, ML, product, customer success, and sales — all full-time in San Francisco.

## Sources
1. [reducto.ai](https://reducto.ai/)
2. [reducto.ai/careers](https://reducto.ai/careers)
3. [ycombinator.com/companies/reducto](https://www.ycombinator.com/companies/reducto)
4. [linkedin.com/company/reducto-ai](https://www.linkedin.com/company/reducto-ai)
5. [cbinsights.com/company/reducto-ai](https://www.cbinsights.com/company/reducto-ai)
6. [fortune.com](https://fortune.com/2025/04/01/reducto-ai-document-parsing-startup-raises-24-5-million-series-a-led-by-benchmark/)

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