SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
OpenAI's Future of Computing Research team is seeking a Machine Learning Engineer to develop multimodal perception and authentication systems for next-generation AI products. This applied research role focuses on how AI systems perceive people and their physical surroundings, combining signals from cameras, microphones, and other sensors.
You will research and develop multimodal perception and authentication methods across visual, audio, and other sensing modalities. The work involves exploring how specialized perception models and larger multimodal models can be integrated effectively, designing data pipelines and training approaches optimized for real-world conditions rather than controlled lab environments.
Key responsibilities include studying model behavior, robustness, and failure modes across different sensing, data, and deployment contexts; integrating and validating new capabilities in real-time or resource-constrained systems; and partnering closely with hardware, firmware, software, and product teams to translate research into working systems.
Ideal candidates have strong backgrounds in computer vision, audio/speech ML, multimodal learning, or sensing systems. You should have experience developing specialized ML models or larger multimodal models, bringing research ideas into practical prototypes or products, and designing rigorous experiments and evaluations. Experience with sensing hardware, real-time systems, deployment constraints, authentication, biometrics, or privacy-sensitive applications is valued. Technical proficiency in Python and PyTorch is required, with comfort in C++ or systems integration preferred.
The role is based in San Francisco with a hybrid schedule (3 days per week in office). OpenAI offers relocation assistance.
