Research Scientist

Key Skills

Deep Learning, Estimation theory, Information Intelligence, Linear Algebra, Mathematical optimization, Optimization, Stochastic models

Job Description

Research Scientist(Palo Alto, CA – multiple positions)

​Conduct applied research and product development with a focus on ML and AI technologies using mathematical and analytical theories, techniques and tools.

Specific duties include:

• Developing mathematical models pertaining to deep learning models that mitigate catastrophic forgetting via non-gradient-based optimization.
• Developing hierarchical models of representation that capture regularities in observations and map those to a decision space whereby each layer of the hierarchy corresponds to a different spatiotemporal scale.
• Employing mathematical techniques derived from stochastic processes, linear algebra, estimation theory, and information theory.
• Developing and evaluating applied research code, including devising simulation and testing environments to illustrate the capabilities of new machine learning algorithms and architectures in various problem domains, including those involving visual and auditory input streams.

REQ: MS or foreign equivalent in Computer Science, Electrical Engineering, Applied Mathematics, or closely related field.

Must have knowledge of linear algebra, calculus, and stochastic processes; machine learning theory and practice, including supervised and unsupervised learning algorithms, reinforcement learning, and sequential decision-making under uncertainty; and mathematical modeling techniques and data science, including classification and regression methods, regularization techniques, and ensemble learning methodologies.

Must also have 2 years of experience (either in graduate school or post-graduate studies) with Python and PyTorch. Experience can be concurrent.

Send cover letter with resume to: I. Arel at Tenyx, 455B Portage Avenue, Palo Alto, CA 94306 or via email: itamar@tenyx.com. No calls.