Research Scientist

Tenyx delivers voice AI agents that automate customer service for the enterprise, creating solutions that are naturally engaging, capable of understanding context, and able to offer the sense of immediacy found in human interactions. Our journey is guided by a team of AI and machine learning veterans from industry giants like Google LLC, Apple Inc., Amazon.com Inc., IBM Corp., and Salesforce Inc. At the heart of our mission lies the delivery of voice AI agents that redefine customer service for enterprises. Join us in reshaping the future of customer service with technology that speaks to the needs of both businesses and their clientele.

As a Research Scientist at Tenyx, you will conduct applied research and product development with a focus on ML and AI technologies, utilizing mathematical and analytical theories, techniques, and tools. You will contribute to the advancement of deep learning models, mathematical modeling techniques, and data science methodologies to enhance our voice AI products.

• Develop mathematical models pertaining to deep learning models that mitigate catastrophic forgetting via non-gradient-based optimization.
• Develop 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.
• Employ mathematical techniques derived from stochastic processes, linear algebra, estimation theory, and information theory.
• Develop and evaluate 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.

• MS or foreign equivalent in Computer Science, Electrical Engineering, Applied Mathematics, or closely related field.
• Knowledge of linear algebra, calculus, and stochastic processes.
• Proficiency in machine learning theory and practice, including supervised and unsupervised learning algorithms, reinforcement learning, and sequential decision-making under uncertainty.
• Familiarity with mathematical modeling techniques and data science methodologies, including classification and regression methods, regularization techniques, and ensemble learning methodologies.
• Minimum of 2 years of experience (either in graduate school or post-graduate studies) with Python and PyTorch.

At Tenyx, we prioritize your well-being and growth with a robust benefits package. Enjoy retirement benefits, comprehensive health coverage, and unlimited vacation flexibility. Stay active with gym reimbursement and become a stakeholder with company equity. Our hybrid work environment offers the best of both worlds, promoting productivity and flexibility. Apply now to be part of our team!