Software Engineer, Infrastructure - Analytics
@ OpenAI

San Francisco, CA
$150,000
On Site
Full Time
Posted 1 day ago

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XXXXXXXXX XXXXXXXXX XXXXXXXXXX****** @openai.com
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Job Details

About The Team

The Scaling team designs, builds, and operates critical infrastructure that enables research at OpenAI, accelerating the progress of research towards AGI by building core systems that researchers rely on.

About The Role

This generalist software engineering role emphasizes distributed systems, data processing infrastructure, and operational excellence. You will develop and operate foundational backend services that underpin OpenAI’s research workflows by creating new infrastructure and enhancing existing systems.

  • Design and build scalable backend systems for ML research.
  • Develop reliable infrastructure supporting streaming and batch data processing.
  • Create internal-facing tools and applications as needed.
  • Debug and optimize Kubernetes services with operational tooling.
  • Participate in on-call rotations to improve system reliability.

You Might Thrive In This Role If You Have

  • Strong proficiency in Python or Rust for backend development.
  • Experience with distributed systems and scalable data processing.
  • Hands-on knowledge of Kubernetes, Terraform, and Helm.
  • A holistic approach from low-level infrastructure to application logic.
  • Curiosity and adaptability in fast-paced, high-growth environments.

Key Skills/Competency

Python, Rust, Distributed Systems, Kubernetes, Terraform, Helm, Kafka, Spark, Data Processing, Observability

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How to Get Hired at OpenAI

🎯 Tips for Getting Hired

  • Customize your resume: Tailor your skills to backend systems.
  • Research OpenAI: Understand their mission and tech stack.
  • Highlight distributed systems: Emphasize relevant experiences.
  • Prepare for technical questions: Review Kubernetes and data processing.
  • Practice behavioral questions: Align with team collaboration stories.

📝 Interview Preparation Advice

Technical Preparation

Review Python and Rust best practices.
Practice designing distributed systems architectures.
Study Kubernetes deployment and Helm usage.
Optimize data streaming and batch processing methods.

Behavioral Questions

Describe collaboration experiences effectively.
Explain problem-solving under pressure.
Share examples of adaptive work strategies.
Discuss time management in fast environments.

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