Multimodal Perception & Authentication ML Engineer

OpenAI

United States

Hybrid

USD 140,000 - 210,000

Full time

14 days+
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Benefits offered by this job

Relocation assistance

Job summary

OpenAI's Future of Computing Research team in San Francisco is seeking a machine learning engineer to help shape how AI systems understand the physical world and the people in it.

You will focus on multimodal perception and authentication, bringing together signals from cameras, microphones, and other sensors, and working with hardware, firmware, software, and product teams to turn research into real-world systems.

Qualifications

  • Strong background in computer vision, audio or speech machine learning, multimodal learning, or sensing.
  • Experience developing specialized ML models, larger multimodal models, or both.
  • Experience bringing research ideas into practical systems, prototypes, or products.
  • Know how to design experiments, build evaluations, and investigate model behavior.

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.

Skills

Computer vision
Audio or speech ML
Multimodal learning
Sensing

Job description

OpenAI's Future of Computing Research team in San Francisco is seeking a machine learning engineer to help shape how AI systems understand the physical world and the people in it.

You will focus on multimodal perception and authentication, bringing together signals from cameras, microphones, and other sensors, and working with hardware, firmware, software, and product teams to turn research into real-world systems.

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