Operating Systems Engineer, Connectivity & Networking | Consumer Devices
OpenAI · San Francisco
CHECKED 23H AGO
Frontier labonsite$230k–$385k
At a glance
Highlights
- Design OS connectivity foundations for next-gen AI consumer devices.
- Build secure, efficient communication across OpenAI products and systems.
- Validate real-world reliability with diagnostic tools and automated tests.
What they offer
- Equity
Ideal candidate
A systems-minded engineer who loves owning connectivity end-to-end, from investigation to shipped product. You thrive debugging across stacks and partnering with hardware and platform teams to build reliable, secure consumer devices.
Requirements
- Substantial hands-on experience developing Wi-Fi and Bluetooth functionality in operating-system frameworks, system services, or connectivity middleware.
- Strong understanding of IP networking, including IPv4/IPv6, TCP/UDP, DNS, DHCP, routing, and socket behavior, with practical experience implementing and debugging networked systems.
- Experience implementing advanced networking capabilities in one or more areas such as routing and network policy, VPNs and tunneling, traffic management, or network isolation.
- Experience designing and maintaining platform APIs and the services behind them, including connection lifecycle management and integration with other OS components.
- Proficiency in C++ for systems development, including concurrent programming, memory ownership, and resource lifetime management.
- Strong understanding of asynchronous systems, interprocess communication, and failure handling.
- Experience diagnosing complex connectivity issues using system traces, protocol captures, logs, and structured debugging.
- Ability to work across disciplines, make sound technical tradeoffs, and carry solutions from investigation through implementation and validation.
Lab profile
About OpenAI
Builds safe frontier AI models and products like ChatGPT for broad benefit.
What they build
- ChatGPT
- OpenAI API
- Frontier AI models
Known for
- Frontier-scale distributed ML training
- Massive GPU fleet and data center operations
- Exabyte-scale data lakes and streaming
- AI alignment and safety research
Key facts
- Operates one of the world's largest GPU fleets