Location

San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $295K – $555K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

OpenAI’s 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. We're a small, fast-moving team of engineers focused on delivering a world-class developer experience while pushing the boundaries of what AI can do.

We’re expanding into multimodal inference, building the infrastructure needed to serve models that handle image, audio, and other non-text 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

We’re looking for a software engineer to help us serve OpenAI’s multimodal models at scale. You’ll be part of a small team responsible for building reliable, high-performance infrastructure for serving real-time audio, image, and other MM workloads in production.

This work is inherently cross-functional: you’ll collaborate directly with researchers training these models and with product teams defining new modalities of interaction. You'll 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 large-scale multimodal models.

• Optimize systems for high-throughput, low-latency 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 state-of-the-art capabilities.

• Contribute to system-level 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 GPU-based ML workloads and understand the performance dynamics of large models, especially with complex data like images or audio.

• Enjoy experimental, fast-evolving work and collaborating closely with research.

• Are comfortable dealing with systems that span networking, distributed compute, and high-throughput data handling.

• Have familiarity with inference tooling like vLLM, TensorRT-LLM, or custom model parallel systems.

• Own problems end-to-end and are excited to operate in ambiguous, fast-moving spaces.

Nice to Have:

• Experience working with image generation or audio synthesis models in production.

• Exposure to distributed ML training or system-efficient model design.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose 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.

XML job scraping automation by YubHub

Microsoft AI are looking for a talented Member of Technical Staff, Multimodal Infrastructure to help build the next wave of capabilities of our personalized AI assistant, Copilot. We're looking for someone who will bring an abundance of positive energy, empathy, and kindness to the team every day, in addition to being highly effective.

About the Role

We're looking for someone who will design, develop and maintain large-scale multimodal data processing pipelines, model pretraining and post-training frameworks, and model inference and serving frameworks. You will work closely with research scientists and product engineers on multimodal data processing, model training, inference and serving tasks. As a contributing member of the core group of engineers, you would also bring to the table best practices driving architectural changes and influence roadmap of relevant software and hardware components.

Accountabilities

• Design, develop and maintain large-scale multimodal data processing pipelines.
• Design, develop and maintain large-scale multimodal model pretraining and post-training frameworks.
• Design, develop and maintain large-scale multimodal model inference and serving frameworks.

The Candidate we're looking for

Experience:

• Bachelor's Degree in Computer Science, or related technical discipline AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Strong proficiency in distributed data processing infra (resource utilization management, fault tolerance, ray & spark) and CPU/GPU batch processing optimizations.
• Experience with state-of-art model inference and serving frameworks.
• Experience with image/video/audio data processing.
• Experience with common data formats for efficient I/O.

Personal attributes:

• Enjoy working in a fast-paced, design-driven, product development cycle.
• Embody our Culture and Values.

Benefits

• Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location.
• Comprehensive health and wellbeing benefits.
• Professional development opportunities.
• Financial benefits (bonus, equity, pension, etc.).

XML job scraping automation by YubHub

Microsoft AI are looking for a talented Member of Technical Staff, Multimodal Infrastructure to help build the next wave of capabilities of our personalized AI assistant, Copilot. We’re looking for someone who will bring an abundance of positive energy, empathy, and kindness to the team every day, in addition to being highly effective.

About the Role

As a Member of Technical Staff, Multimodal Infrastructure, you will be responsible for designing, developing, and maintaining large-scale multimodal data processing pipelines, model pretraining and post-training frameworks, and model inference and serving frameworks. You will work closely with research scientists and product engineers to solve infra-related problems and find a path to get things done despite roadblocks to get your work into the hands of users quickly and iteratively.

Accountabilities

• Design, develop, and maintain large-scale multimodal data processing pipelines.
• Design, develop, and maintain large-scale multimodal model pretraining and post-training frameworks.
• Design, develop, and maintain large-scale multimodal model inference and serving frameworks.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Computer Science, or related technical discipline AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Strong proficiency in distributed data processing infra (resource utilization management, fault tolerance, ray & spark) and CPU/GPU batch processing optimizations.
• Experience with state-of-art model inference and serving frameworks.
• Experience with image/video/audio data processing.
• Experience with common data formats for efficient I/O.

Personal attributes:

• Enjoy working in a fast-paced, design-driven, product development cycle.
• Embody our Culture and Values.

Benefits

• Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location.
• Comprehensive health and wellbeing benefits.
• Professional development opportunities.
• Financial benefits (bonus, equity, pension, etc.).

XML job scraping automation by YubHub