Software Engineer Systems Research Internship, Applied Emerging Talent (Summer 2026)

OpenAI • San Francisco, CA

2d • Onsite

About The Position

A systems research internship is for people who love the real-world intersection of systems-engineering and research: you’ll investigate a hard systems problem, build something meaningful, and measure it carefully. The goal is practical impact—making Applied Systems better: more efficient, more scalable, and more reliable.
OpenAI is currently recruiting for candidates interested in a 13-week, paid, in-person internship based in our San Francisco office during Summer 2026. In some cases, it may be extended for an additional 13 weeks (for a total of up to 26 weeks), based on team needs, candidate interest, and performance.
In this role, you will typically focus on improving real systems in areas like:
Distributed systems & storage (throughput, latency, consistency, durability)
Compute & scheduling (GPU/accelerator utilization, job orchestration, queuing)
Performance engineering (profiling, bottlenecks, scalability, capacity planning)
Reliability & observability (fault tolerance, monitoring, incident learning)
Networking & data pipelines (data movement, caching, streaming efficiency)
Systems for ML (training/inference performance, evaluation infrastructure, tooling)
Most projects involve some of these steps:
Defining a clear hypothesis (“we think X will reduce latency by Y under Z”)
Instrumenting existing production systems, gathering metrics and detailed analysis to validate the hypothesis
Building or modifying a real system (prototype or production-quality improvements when appropriate)
Running experiments/benchmarks and analyzing results
Communicating tradeoffs and recommendations clearly
Publishing the research work in technical journals and conferences

Requirements

• Currently pursuing a PhD in Computer Science, Computer Engineering, or relevant technical field
• Proficiency with Coding in c++, Java, python, rust, etc
• Doing ongoing research on systems topics such as DL/ML, information retrieval, systems security and cryptography, databases, networking, distributed systems, and compilers, etc
• Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines

Responsibilities

• Defining a clear hypothesis (“we think X will reduce latency by Y under Z”)
• Instrumenting existing production systems, gathering metrics and detailed analysis to validate the hypothesis
• Building or modifying a real system (prototype or production-quality improvements when appropriate)
• Running experiments/benchmarks and analyzing results
• Communicating tradeoffs and recommendations clearly
• Publishing the research work in technical journals and conferences

What This Job Offers

• Career Level: Intern
• Education Level: Ph.D. or professional degree