<?xml version="1.0" encoding="UTF-8"?>
<source>
  <jobs>
    <job>
      <externalid>4075c787-328</externalid>
      <Title>Member of Technical Staff - Large Scale Data Infrastructure</Title>
      <Description><![CDATA[<p>We&#39;re looking for infrastructure engineers to work at peta-to-exabyte scale. You&#39;ll build data systems behind the largest training runs on thousands of GPUs, where fixing one bottleneck lets researchers train the next breakthrough model.</p>
<p><strong>What You&#39;ll Work On:</strong></p>
<ul>
<li>Scalable data loaders for training runs across thousands of GPUs</li>
<li>Efficient storage and retrieval systems for petabyte-scale datasets</li>
<li>Multi-cloud object storage abstraction</li>
<li>Execute large-scale data migrations across storage systems and providers</li>
<li>Debug and resolve performance bottlenecks in distributed data loading</li>
</ul>
<p><strong>Technical Focus:</strong></p>
<ul>
<li>Python, PyTorch DataLoader internals</li>
<li>Object storage (e.g. S3, Azure Blob, GCS)</li>
<li>Parquet for metadata</li>
<li>Video: ffmpeg, PyAV, codec fundamentals</li>
</ul>
<p><strong>What We&#39;re Looking For:</strong></p>
<ul>
<li>Built and operated data pipelines at petabyte scale</li>
<li>Optimized data loading</li>
<li>Worked with petabyte-scale video and image datasets</li>
<li>Written processing jobs operating on millions of files</li>
<li>Debugged distributed system bottlenecks across large fleets of machines</li>
</ul>
<p><strong>Nice to Have:</strong></p>
<ul>
<li>Experience streaming dataset formats (e.g. WebDataset)</li>
<li>Video codec internals and frame-accurate seeking</li>
<li>Distributed systems experience</li>
<li>Slurm and Kubernetes for job orchestration</li>
<li>Experience with object storage performance tuning across providers</li>
</ul>
<p><strong>How We Work Together:</strong></p>
<ul>
<li>We&#39;re a distributed team with real offices that people actually use. Depending on your role, you&#39;ll either join us in Freiburg or SF at least 2 days a week (or one full week every other week), or work remotely with a monthly in-person week to stay connected. We&#39;ll cover reasonable travel costs to make this possible. We think in-person time matters, and we&#39;ve structured things to make it accessible to all. We&#39;ll discuss what this will look like for the role during our interview process.</li>
</ul>
<p><strong>Everything we do is grounded in four values:</strong></p>
<ul>
<li>Obsessed. We are a frontier research lab. The science has to be right, the understanding deep, the product beautiful.</li>
<li>Low Ego. The work speaks. The best idea wins, no matter who said it. Credit is shared. Nobody is above any task.</li>
<li>Bold. We take the ambitious bet. We ship, we do not wait for conditions to be perfect.</li>
<li>Kind. People over politics. We treat each other with genuine warmth. Agency without empathy creates chaos.</li>
</ul>
<p style="margin-top:24px;font-size:13px;color:#666;">XML job scraping automation by <a href="https://yubhub.co">YubHub</a></p>]]></Description>
      <Jobtype>full-time</Jobtype>
      <Experiencelevel>staff</Experiencelevel>
      <Workarrangement>hybrid</Workarrangement>
      <Salaryrange>$180,000–$300,000 USD + Equity</Salaryrange>
      <Skills>Python, PyTorch, Data Loader Internals, Object Storage, Parquet, Video, ffmpeg, PyAV, Codec Fundamentals, WebDataset, Distributed Systems, Slurm, Kubernetes, Object Storage Performance Tuning</Skills>
      <Category>Engineering</Category>
      <Industry>Technology</Industry>
      <Employername>Black Forest Labs</Employername>
      <Employerlogo>https://logos.yubhub.co/blackforestlabs.com.png</Employerlogo>
      <Employerdescription>Black Forest Labs is a research lab developing foundational technologies for generative models that power image and video creation.</Employerdescription>
      <Employerwebsite>https://www.blackforestlabs.com/</Employerwebsite>
      <Compensationcurrency></Compensationcurrency>
      <Compensationmin></Compensationmin>
      <Compensationmax></Compensationmax>
      <Applyto>https://job-boards.greenhouse.io/blackforestlabs/jobs/5019171008</Applyto>
      <Location>Freiburg (Germany), San Francisco (USA)</Location>
      <Country></Country>
      <Postedate>2026-04-17</Postedate>
    </job>
  </jobs>
</source>