Axiomatic AI develops AI-powered verification infrastructure that automates and validates complex engineering and scientific workflows.
<p><strong>About us: <br></strong></p> <p>Axiomatic AI is building a new class of AI systems designed to reason with the rigor of the scientific method. By combining deep learning with formal logic and physics-based modeling, we create verifiable, interpretable AI systems that collaborate with and support human researchers in high-stakes scientific and engineering workflows. </p> <p><strong>Our mission, 30×30</strong>, is to deliver a 30× improvement in the speed, accessibility, and cost of semiconductor and photonic hardware development by 2030. </p> <p>We aim to revolutionize hardware design and simulation in these industries and are building a team of highly motivated professionals to bring these innovations from research into commercial products.</p> <p><strong>Position overview: </strong></p> <p>As an AI Research Scientist with focus on scientific reasoning, you will join a focused team, playing a key role in building new techniques for enabling reliable and trustworthy AI applications for science and engineering. Your responsibilities will include developing formal and informal verification pipelines for scientific reasoning, data analysis and curation, conducting systematic benchmarking to evaluate performance, analyze design flaws and propose solutions. Close collaboration with our dedicated cross-functional team, consisting of Mathematicians, AI Engineers, Software Engineers, Lean4 developers, Physicists and AI scientists, will be essential to the success of the project.</p> <p><strong>Your mission:</strong></p> <ul> <li><strong>Project contribution and technical execution:</strong> Play an active role in designing and developing formalization and validation strategies specifically tailored for scientific applications.</li> <li><strong>Innovation & continuous learning: </strong>Stay updated with state-of-the-art techniques and advancements in the field. Continuously integrate the latest research and technologies to enhance the products’ impact.</li> <li><strong>Cross-team collaboration: </strong>Work closely with AI and development teams to ensure seamless integration of solutions. Promote open communication and cooperation to enhance productivity and technical excellence.</li> <li><strong>Knowledge sharing and developing the team:</strong> Foster a collaborative culture by actively sharing knowledge, insights, and best practices. Encourage teamwork and continuous learning to strengthen overall expertise within the company.</li> </ul> <p><strong>About You:</strong></p> <ul> <li>You are highly motivated, hard-working, and committed to personal and professional growth through constant learning, new challenges and advancements.</li> <li>You quickly grasp new concepts and technologies, adapting efficiently to evolving requirements.</li> <li>You have a real passion for science and maths, and have a deep curiosity for understanding concepts from first principles.</li> <li>You excel as a team player, thriving in multidisciplinary and multicultural environments.</li> <li>You enjoy working in a dynamic, fast-paced environment, embracing change with a proactive and solution-oriented approach, you thrive in ambiguities.</li> </ul> <p><strong>Key requirements:</strong></p> <ul> <li>PhD in Computer Science, Artificial Intelligence, Machine Learning or related fields.</li> <li>Experience in applications of machine learning to relevant projects and publications at top-tier conferences.</li> <li>Proficient in Python, with the ability to write clean and efficient code in shared code bases</li> <li>Experienced with major deep learning and agentic AI frameworks</li> <li>Solid understanding of statistics and probability</li> </ul> <p><strong>Nice to have:</strong></p> <ul> <li>Background in Physics, Engineering or other related computational science.</li> <li>Internship or work experience in one top AI company.</li> <li>Strong experience in at least one of the following: agentic LLMs and RAG, machine learning for science, program synthesis, NLP, training and fine-tuning LLMs, knowledge graphs, applied machine learning, machine learning for theorem proving, graph machine learning, reinforcement learning, representation learning.</li> <li>Proven contribution to open source projects.</li> </ul> <p> </p> <p><strong>What we offer:</strong></p> <ul> <li><strong>Competitive compensation</strong></li> <li><strong>Stock Options Plan:</strong> Empowering you to share in our success and growth.</li> <li><strong>Cutting-Edge Tools:</strong> Access to state-of-the-art tools and collaborative opportunities with leading experts in artificial intelligence, physics, hardware and electronic design automation.</li> <li><strong>Professional Growth:</strong> Opportunities to attend industry conferences, present research findings, and engage with the global AI research community.</li> <li><strong>Impact-Driven Culture: </strong>Join a passionate team focused on solving some of the most challenging problems at the intersection of AI and hardware.</li> </ul> <p><strong><br>Work model: </strong>Hybrid <br><br></p> <p><strong>Why join us? </strong></p> <p>At Axiomatic_AI, you will be working on technology that drives innovation in AI for scientific and engineering applications in line with our 30 x 30 mission. This is your opportunity to contribute to the development of new AI architectures that can reason coherently and produce interpretable and verifiable solutions. Consequently, see those ideas commercialized into products that will shape the future of hardware and computing, while collaborating with a global team of engineers and AI specialists. We believe in pushing the boundaries of what is possible and continuously seek to redefine the intersection of AI, with focus on formal consistency. If you're ready to take your expertise in artificial intelligence and physics to the next level, we want to hear from you!<span style="color: rgb(236, 240, 241);"> <span style="color: rgb(255,