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As a Connectivity Software Engineer, you'll design and optimize wireless connectivity solutions, implement features, troubleshoot protocols, and enhance performance across OpenAI's products.

As a Software Engineer on the Caching Infrastructure team, you will design, build, and operate a multi-tenant caching platform that scales and meets various use cases, ensuring performance and reliability.

This role involves analyzing inference performance, building models, and optimizing systems for better latency and cost efficiency.

As a Full Stack Software Engineer, you will drive growth initiatives for ChatGPT through data analysis, product ideation, and API development, while collaborating with diverse teams to enhance user experiences.

The role involves driving strategic and operational initiatives in customer support, collaborating with various teams to enhance customer experience and optimize operations, with a focus on leveraging AI.

Profile, benchmark, and optimize embedded hardware product performance across OS, application, camera/vision, graphics, and platform stacks. Build benchmarking methodologies and tooling, define KPIs and measurement frameworks, investigate field regressions, and partner with cross-functional teams to drive performance improvements from lab characterization through product launch and real-world usage.

Build and own full-stack features for ChatGPT Finances, from frontend experiences to backend services and data models. Design secure APIs, resilient integrations, and AI-driven, grounded conversational financial capabilities. Ensure performance, accessibility, observability, and system reliability while collaborating across product, design, infrastructure, security, and data teams.

Lead sourcing strategies to identify and engage top-tier engineering talent, build and maintain pipelines of passive candidates, collaborate with hiring managers, use advanced sourcing tools, represent OpenAI at events, and maintain candidate data and metrics to inform hiring.

Design and run empirical experiments to measure and improve chain-of-thought and model monitorability. Build evaluations and monitoring methods, analyze model behavior, investigate training interventions, translate findings into oversight and training recommendations, collaborate across research and engineering teams, and publish results that advance alignment science.

Design and build systems that automate and accelerate research workflows: evaluations, data and evaluation flywheels, agent harnesses, RL environments, experiment orchestration, sandboxed runtimes, integrations with research infrastructure, and metrics to measure research productivity and safety.