Machine Learning Engineer, Multimodal Perception and Authentication
Develop multimodal perception and authentication systems combining visual, audio, and other sensor signals for real-world AI products. The role requires machine learning expertise, practical research-to-system experience, and proficiency in Python and PyTorch with comfort in C++.
About the job
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 to 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.
- Collaborate 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.
- Experience bringing research ideas into practical systems, prototypes, or products.
- Ability to design experiments, build evaluations, and investigate model behavior.
- Experience with sensing hardware, real-time systems, or other deployment constraints.
- Proficiency in Python and PyTorch, with comfort in C++ or systems integration.
- Experience with authentication, biometrics, or other privacy-sensitive applications.
- Ability to work across disciplines on developing research problems.
Skills
Python, PyTorch, C++, Computer Vision, Audio Machine Learning, Speech Machine Learning, Multimodal Learning, Authentication, Biometrics, Real-Time Systems, Systems Integration, Model Evaluation
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