AI Resident

Summary

The job is an AI Research Residency at Normal Computing, lasting 6-12 months with the possibility of extension. The role involves developing cutting-edge AI algorithms and hardware paradigms for a physics-based AI platform. The position can be based in New York or remote.

Requirements

• Experience with large-scale numerical simulations, including benchmarking of ML algorithms and training of ML models
• Experience with modern AI methods, such as probabilistic ML, Bayesian reasoning, sampling algorithms, and generative AI models
• Familiarity with classical physics formalism, differential equations, and stochastic processes
• Familiarity with characterizing the impact of noise and imperfections on algorithmic performance
• Familiarity with data science applications and specific use cases of ML methods
• Proficiency in at least one programming language, with a preference for those commonly used in ML or scientific computing such as Python or C++
• Familiarity with TensorFlow, PyTorch, Jax, NumPy, Pandas, or similar ML/scientific libraries

Responsibilities

• Interface with our world-class research team focused on developing a full-stack physics-based AI platform
• Explore cutting-edge generative AI tools for novel applications
• Research and develop new algorithms and hardware paradigms for AI
• Conduct numerical benchmarking of algorithmic and hardware proposals
• Optimize hardware speedups over state-of-the-art and characterize the impact of hardware noise
• Investigate commercial applications that stand to benefit from Normal’s physics-based AI platform

Benefits

• Competitive salary
• Benefits including medical (Depending on location)
• Opportunity to explore a full-time role at Normal Computing after the residency