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You will be updated with latest job alerts via emailUSD 310000 - 460000
1 Vacancy
About the Team
OpenAIs Inference team powers the deployment of our most advanced models including our GPT models 4o Image Generation and Whisper across a variety of platforms. Our work ensures these models are available performant and scalable in production and we partner closely with Research to bring the next generation of models into the world. Were a small fastmoving team of engineers focused on delivering a worldclass developer experience while pushing the boundaries of what AI can do.
Were expanding into multimodal inference building the infrastructure needed to serve models that handle image audio and other nontext modalities. These workloads are inherently more heterogeneous and experimental involving diverse model sizes and interactions more complex input/output formats and tighter coordination with product and research.
About the Role
Were looking for a software engineer to help us serve OpenAIs multimodal models at scale. Youll be part of a small team responsible for building reliable highperformance infrastructure for serving realtime audio image and other MM workloads in production.
This work is inherently crossfunctional: youll collaborate directly with researchers training these models and with product teams defining new modalities of interaction. Youll build and optimize the systems that let users generate speech understand images and interact with models in ways far beyond text.
In this role you will:
Design and implement inference infrastructure for largescale multimodal models.
Optimize systems for highthroughput lowlatency delivery of image and audio inputs and outputs.
Enable experimental research workflows to transition into reliable production services.
Collaborate closely with researchers infra teams and product engineers to deploy stateoftheart capabilities.
Contribute to systemlevel improvements including GPU utilization tensor parallelism and hardware abstraction layers.
You might thrive in this role if you:
Have experience building and scaling inference systems for LLMs or multimodal models.
Have worked with GPUbased ML workloads and understand the performance dynamics of large models especially with complex data like images or audio.
Enjoy experimental fastevolving work and collaborating closely with research.
Are comfortable dealing with systems that span networking distributed compute and highthroughput data handling.
Have familiarity with inference tooling like vLLM TensorRTLLM or custom model parallel systems.
Own problems endtoend and are excited to operate in ambiguous fastmoving spaces.
Nice to Have:
Experience working with image generation or audio synthesis models in production.
Exposure to distributed ML training or systemefficient model design.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that generalpurpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core and to achieve our mission we must encompass and value the many different perspectives voices and experiences that form the full spectrum of humanity.
We are an equal opportunity employer and do not discriminate on the basis of race religion national origin gender sexual orientation age veteran status disability or any other legally protected status.
OpenAI Affirmative Action and Equal Employment Opportunity Policy Statement
For US Based Candidates: Pursuant to the San Francisco Fair Chance Ordinance we will consider qualified applicants with arrest and conviction records.
We are committed to providing reasonable accommodations to applicants with disabilities and requests can be made via thislink.
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At OpenAI we believe artificial intelligence has the potential to help people solve immense global challenges and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Full-Time