Reducto Logo

Reducto

Machine Learning Infra Engineer

Reposted 20 Days Ago
In-Office
San Francisco, CA, USA
150K-300K Annually
Mid level
In-Office
San Francisco, CA, USA
150K-300K Annually
Mid level
As an ML Infra Engineer, you'll build and maintain training and inference frameworks, scale distributed workloads, and improve system observability. You'll apply state-of-the-art methods while collaborating with ML and Platform teams.
The summary above was generated by AI
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.

 

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.

 
 
HQ

Reducto San Francisco, California, USA Office

San Francisco, CA, United States

Similar Jobs

4 Days Ago
In-Office
Mountain View, CA, USA
174K-299K Annually
Senior level
174K-299K Annually
Senior level
eCommerce
Design and implement scalable offline and online ML infrastructure for Search & Discovery: build data logging, ETL, training pipelines, and real-time model serving for ranking and recommendations, collaborate with cross-functional teams, and mentor engineers.
Top Skills: Apache AirflowAWSGCPHadoopHiveJavaPrestoPythonPyTorchScalaSparkTensorFlow
10 Days Ago
In-Office
San Francisco, CA, USA
Junior
Junior
Agency • Artificial Intelligence • HR Tech • Professional Services
Build and scale backend systems and cloud-native infrastructure for large-scale ML workloads. Implement distributed training/inference pipelines, developer tools, and observability for GPU-heavy jobs while collaborating with ML engineers.
Top Skills: ContainersDockerGoGpu WorkloadsKubernetesPythonRaySglangVllm
12 Days Ago
In-Office
San Francisco, CA, USA
Mid level
Mid level
Artificial Intelligence • Logistics • Robotics • Transportation
Design, build, and scale ML infrastructure: ingest vehicle sensor data, create batch pipelines for dataset curation, run distributed GPU training, and ensure performance, observability, efficiency, and security across the ML pipeline while partnering with ML teams.
Top Skills: AnsibleCi/CdCloud InfrastructureCluster Scheduling SystemsCryptographyGpu ClustersLinuxNetwork SecurityTerraform

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account