Machine Learning Researcher / Mathematician in Formal Methods

Machine Learning Researcher / Mathematician in Formal Methods

Axiomatic_AI's mission:

Axiomatic_AI is launching with the aim to accelerate R&D by "Automated Interpretable Reasoning" (AIR) -- a verifiably truthful AI model built for reasoning in science and engineering. Axiomatic_AI is hiring top talent interested in a future of human reasoning aided by -- not replaced by -- AI, and a future that empowers a new generation of innovators to solve important problems through deep-tech engineering in the semiconductor ecosystem.

Responsibilities:

1. Test methods for automated design and measurements
2. Collaborate with machine learning and chip design experts to develop AIR
3. Develop the AIR platform for use by the customers
4. Actively engage in the understanding of cutting-edge AI and machine learning methods

Qualifications:

1. B.S. in computer science, statistics, computer engineering, or electrical engineering or related discipline
2. Experience in machine learning methods such as neural networks, reinforcement learning, large language models through coursework and projects
3. Excellent programming skills in Python
4. Demonstrated ability to work collaboratively in a multidisciplinary team
5. Excellent analytical and problem-solving skills
6. Excellent written and oral communication skills
7. Excellent foundation in the physical sciences and knowledge of deep-tech industries are a significant plus.

What We Offer:

1. A competitive compensation package, including equity in a VC-backed startup.
2. Comprehensive benefits, and a flexible PTO policy.
3. An opportunity to be part of a groundbreaking company from its stealth phase through to public launch and beyond.
4. The opportunity to work on pioneering projects that blend scientific research with practical hardware design
5. A culture of learning & innovation ideal for professional development
6. A fast-paced, highly dynamic and interdisciplinary work environment