Machine Learning Engineer, Multimodal Perception and Authentication

About the Team

The Future of Computing Research team is an applied research team within OpenAI’s Consumer Devices group. We study how AI systems perceive people and their surroundings, and we turn that research into capabilities for future products.

Our work spans machine learning, sensing, and hardware, with a focus on building systems that work beyond controlled environments.

About the Role

We’re looking for a machine learning engineer to help shape how future AI systems understand the physical world and the people in it. The role focuses on multimodal perception and authentication, bringing together signals from cameras, microphones, and other sensors.

You’ll work with specialized perception models and larger multimodal models, and partner with hardware, firmware, software, and product teams to bring new research into real-world systems.

This role is based in San Francisco. We work in the office three days per week and offer relocation assistance.

In this role, you will

• Research and develop multimodal perception and authentication methods across visual, audio, and other sensing signals.

• Explore how specialized perception models and larger multimodal models can work together.

• Design data, training, and evaluation approaches that improve performance in real-world conditions.

• Study model behavior, robustness, and failure modes across sensing, data, and deployment environments.

• Integrate and validate new capabilities in real-time or resource-constrained systems.

• Work with hardware, firmware, software, and product teams to turn research into working systems.

You might thrive in this role if you

• Have a strong background in computer vision, audio or speech machine learning, multimodal learning, or sensing.

• Have experience developing specialized machine learning models, larger multimodal models, or both.

• Have brought research ideas into practical systems, prototypes, or products.

• Know how to design experiments, build evaluations, and investigate model behavior.

• Have worked with sensing hardware, real-time systems, or other deployment constraints.

• Are proficient in Python and PyTorch and comfortable with C++ or systems integration.

• Have experience with authentication, biometrics, or other privacy-sensitive applications.

• Enjoy working across disciplines on research problems that are still taking shape.

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.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional off

Responsibilities

• Research and develop multimodal perception and authentication methods across visual, audio, and other sensing signals.
• Explore how specialized perception models and larger multimodal models can work together.
• Design data, training, and evaluation approaches that improve performance in real-world conditions.
• Study model behavior, robustness, and failure modes across sensing, data, and deployment environments.
• Integrate and validate new capabilities in real-time or resource-constrained systems.
• Work with hardware, firmware, software, and product teams to turn research into working systems.

Requirements

• Strong background in computer vision, audio or speech machine learning, multimodal learning, or sensing.
• Experience developing specialized machine learning models, larger multimodal models, or both.
• Brought research ideas into practical systems, prototypes, or products.
• Know how to design experiments, build evaluations, and investigate model behavior.
• Worked with sensing hardware, real-time systems, or other deployment constraints.
• Proficient in Python and PyTorch and comfortable with C++ or systems integration.
• Experience with authentication, biometrics, or other privacy-sensitive applications.
• Enjoy working across disciplines on research problems that are still taking shape.

• Relocation assistance