HRL Laboratories
Machine Learning Engineer - Advanced AI and Cognitive Systems
About this role
HRL Laboratories seeks a Machine Learning Engineer to develop intelligent systems that integrate neurophysiological, behavioral, and sensor data for cognitive-aware decision support. You'll advance multimodal AI, cognitive state estimation, and human-machine collaboration in mission-driven R&D programs.
What you'll do
- Build AI models integrating neurophysiological, behavioral, and sensor data for cognitive decision support
- Develop algorithms for cognitive state estimation and user modeling
- Apply cognitive science principles to improve explainability, trust, and human-AI collaboration
- Contribute to research proposals, technical publications, and invention disclosures
- Demonstrate prototypes and support capability outreach to customers
- Design and implement scalable, containerized ML systems and APIs
What they're looking for
- Machine learning frameworks (PyTorch, TensorFlow, JAX)
- LLMs and multimodal AI (Transformers, RAG, prompt engineering)
- Cognitive state estimation and computational cognitive modeling
- Software engineering and containerization (Docker, Kubernetes)
- Neurophysiological sensing and behavioral analytics
- Feature engineering and statistical modeling in Python
- Human-machine interaction and cognitive architectures
- Government R&D program experience (DARPA/IARPA/ARPA-H)
Benefits
- Medical, dental, and vision insurance
- 401(k) matching
- Life insurance
- On-site gym facilities
- Generous PTO and sick time
- Upward mobility and challenging work environment
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HRL Laboratories
HRL Laboratories develops advanced sensors, actuators, and hardware systems for aerospace, defense, and quantum computing applications, leveraging expertise in MEMS microfabrication, electro-mechanical design, and mixed-signal electronics. The company is hiring process engineers, mechanical designers, and hardware engineers to scale innovative technologies from research prototypes into production-ready systems.
View all jobs at HRL LaboratoriesLikely interview questions
- Describe a project where you integrated multiple data modalities (e.g., sensor, physiological, behavioral) into an ML system—what were the key challenges?
- How have you applied cognitive science principles to improve model interpretability or human trust in AI systems?