About Unconventional

Since 2022, AI has entered the mainstream, reshaping entire industries from education and software development to fundamental consumer behaviors. This revolution has created an unprecedented demand for computation - a demand that is now fundamentally limited by energy, not just in the datacenter, but at a global scale.

At Unconventional, our mission is to solve this. We are rethinking computing from the ground up to build a new foundation for AI that is 1000x more efficient. We're doing this by exploiting the rich physics of semiconductors, mapping neural networks directly to the device physics rather than relying on layers of inefficient abstraction.

The Role

As a Member of Technical Staff, AI Algorithms, you will be a foundational member of our small, multi-disciplinary R&D team. This isn't a role with a predefined checklist; it's an opportunity to help define the "what" and the "how."

We are looking for 'first principles' thinkers with deep understanding of the fundamentals of analog mixed-signal design who are excited to tackle the hardest, most ambiguous technical challenges at the intersection of AI, physics, and computer architecture. You will be responsible for driving invention, prototyping, and validation of the core components of our novel computing platform.

Responsibilities

• Algorithmic and Theoretical Expertise: Apply deep understanding of advanced ML modeling approaches, such as Transformers, Diffusion, Score, Flow-Based Generative Models, Energy-Based Models, Neural ODEs, and Deep Equilibrium Models, including their computational properties and trade-offs.
• Implementation and Optimization: Practically implement, modify, and validate these models. Tackle unique optimization challenges associated with continuous-time and implicit architectures, leveraging expertise in numerical methods for solving systems (e.g., backpropagation through differential equations and fixed-point solvers).
• Cross-Functional Collaboration: Translate complex, cutting-edge concepts into clear requirements and insights for adjacent teams, especially systems and hardware designers.

Minimum Qualifications

• Education: An MS/PhD or equivalent research/project experience in a quantitative field such as AI/Machine Learning, Computer Science, Physics, Electrical Engineering, or Applied Math.
• Experience: Demonstrated technical excellence and expertise in the theory, training, and empirical analysis of next-generation machine learning architectures that exploit continuous-time dynamics and/or implicit representations. This includes, but is not limited to: Transformers, Diffusion, Score, and/or Flow-Based Generative Models Energy-Based Models, Neural Ordinary Differential Equations, and Deep Equilibrium Models.
• Software Development: Fluent in modern deep learning frameworks (e.g., PyTorch or JAX) for development and validation.

Preferred Qualifications (Nice to Have)

• Full-System Experience: Demonstrated ability to debug and solve quality/performance bottlenecks across the entire system stack (algorithms to deep learning frameworks to low-level programming models, such as Triton/CUTLASS/CUDA).
• Unconventional Co-Design: A forward-looking perspective on co-designing algorithms for unconventional computing paradigms that map closely to the physics of underlying systems.

Why Join Us?

• The Mission: Redefine computing for the next 50 years by solving the fundamental energy limitation of AI at a global scale.
• The Impact: Shape the company's future as a foundational team member. Enjoy massive ownership and an outsized opportunity to drive change.
• The Challenge: Dive into deeply complex, intellectually stimulating, and unsolved problems at the cutting edge of multiple, converging fields.
• The Perks: A comprehensive package including best-in-class health benefits, 401k matching, truly unlimited PTO, and complimentary meals in our Palo Alto office.