Machine Learning Engineer - Advanced AI and Cognitive Systems
$140,700–$175,950 year
On-siteCalabasas, California, United States
Job Summary
Lead research, engineering, and software development efforts to build AI models integrating neurophysiological, behavioral, and sensor data for cognitive aware decision support. Develop algorithms for cognitive state estimation and user modeling while applying cognitive science to improve explainability and human AI collaboration. Contribute to proposals, publications, invention disclosures, and customer briefings, then demonstrate prototypes to support capability outreach. This role focuses on machine learning, multimodal AI, and cognitive modeling within a team advancing next-generation intelligent systems for mission-driven R&D programs.
Required Qualifications
- Human Machine Interaction: Cognitive architectures, neurophysiological sensing, behavioral analytics, human subjects methods
- Cognitive Modeling: Cognitive state estimation and computational models
- LLMs & Multimodal AI: Transformers, prompt design, fine tuning, RAG, with emphasis on integrating human state and environmental context
- Software Engineering: Scalable systems, APIs, Docker, and containerized environments (Docker, Kubernetes)
- Machine Learning & AI: Supervised/unsupervised learning, RL; PyTorch/TensorFlow/JAX
- Data Analytics: Feature engineering, statistical modeling in Python
- MS or Ph.D. in Applied Math, Cognitive Science, or related fields
- 3–5 years of applied ML/AI experience
- U.S. Citizenship with the ability to obtain and maintain a U.S. Government Security Clearance
- Strong interdisciplinary communication and collaboration skills
- Ability to work in fast paced, exploratory research environments
- Curiosity driven mindset with a passion for solving complex problems
Desired Qualifications
- Experience with government funded R&D programs (DARPA/IARPA/ARPA H) is a plus
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