Top Tech Jobs & Startup Jobs

The Software Engineer in Systems will design and build distributed systems for training AI models, focusing on efficiency and robustness in the face of hardware failures, and developing tooling for large training jobs on supercomputers.

The Software Engineer will develop customer-facing features for ChatGPT and OpenAI API, collaborating with cross-functional teams to optimize applications for performance and scale. Responsibilities include user interaction for feedback, iterating on solutions, and working closely with research teams to enhance products. Requires strong experience and proficiency in relevant technologies.

As a Full Stack Software Engineer at OpenAI, you'll develop HR and recruiting software while working closely with cross-functional teams. Responsibilities include owning the product lifecycle, collaborating with stakeholders, and applying AI/ML innovations. A background in tech and product-driven companies with strong skills in JavaScript and Python is preferred.

As a Software Engineer on the Frontier Systems Infrastructure team, you will design, operate, and optimize large-scale compute clusters to support advanced AI research. Responsibilities include managing resource allocation, automating cluster operations, and ensuring system reliability and efficiency. Candidates should have a background in distributed systems and strong programming skills.

The role involves architecting and building advanced billing systems, developing comprehensive billing integrations, and designing a versatile billing platform. Collaboration with internal teams and stakeholders is key to ensure scalability and functionality meets customer needs.

As a Frontend Engineer at OpenAI, you will collaborate with research, product, and design teams to develop efficient front-end systems for complex web applications. Your role involves deploying front-end infrastructure and fostering an inclusive culture, with a focus on enhancing user experience and adapting to rapidly changing conditions.

The role involves delivering APIs for distributed computing systems, optimizing performance for large-scale machine learning training workloads, and deploying training frameworks on advanced supercomputers. Collaboration with researchers is key to enhance system efficiency and stability.