infrastructure engineer

Sieve Inc.
San Francisco, CA, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Cloud Computing Computer Programming Continuous Integration Data Infrastructure Extract Transform Load (ETL) Data Systems Distributed Systems Python (Programming Language) Graphics Processing Unit (GPU) Delivery Pipeline

Job description

As an infrastructure engineer at Sieve, you’ll design and engineer systems that handle the compute, scheduling, and orchestration of complex ML + ETL pipelines that need to run quickly, reliably, and cost-effectively on large sums of video.

Requirements

You’re likely a good fit if you love optimizing for system uptime, have worked with cloud technologies, optimizing hyper-fast distributed systems at the scale of thousands of GPUs, and building great internal tooling and CI/CD for rapid iteration., * 3+ years of experience building foundational data infrastructure

  • Proficient in working across diverse cloud architectures
  • Designed and maintained pipelines that process petabytes of data
  • Developed robust CI/CD pipelines tailored for ML-focused teams
  • Strong coding experience with Go and Python; Experience with Rust is a plus
  • Operates as an IC who leads by example
  • Experience with large-scale video data systems
  • In-person at our SF HQ

About the company

Sieve is a multi-modal lab curating the world’s highest-quality training datasets - spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data., Sieve is one of the most capital-efficient teams in AI - roughly 30 people serving the world’s leading AI labs across every major data modality. You’ll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.

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