AI Scientist

AI Scientist – AI Retrieval Systems and Knowledge Graphs About us: Axiomatic_AI is dedicated to accelerating R&D by developing the next generation of Automated Interpretable Reasoning, a verifiably truthful AI model built for reasoning in science and engineering, empowering engineers specifically in hardware design and Electronic Design Automation (EDA), with a mission to revolutionize the fields of hardware design and simulation in the photonics and semiconductor industry. We seek highly motivated professionals to help us bring these innovations to life, driving the evolution from development to commercial product. Position overview As an AI Scientist specialized in retrieval systems and knowledge graphs, you will play a key role in developing Axiomatic’s verifiable scientific reasoning. Your responsibilities include designing, prototyping, developing, testing and iterating on the core architecture. You will also manage data curation, conduct benchmarking to evaluate performance, analyze reasoning flaws and propose solutions. Close collaboration with our focused cross‑functional team—AI Engineers, Software Engineers, Physicists and AI scientists—and regular alignment with customer and business needs will be essential. Your mission AI Research and Development: Contribute to the development of validated AI reasoning models and architectures, focusing on automated reasoning techniques and application to scientific fields where rigor and reliability are fundamental. Data & Benchmarking: Supervise dataset curation, run benchmarks, and analyze performance results to guide improvements. Collaboration: Work closely with a cross‑functional team of engineers and scientists, collaborating on solving challenging problems at the intersection of AI, physics and engineering. Documentation and Reporting: Develop detailed technical documentation and present research findings to internal teams and external stakeholders. Research & Publication: Contribute to cutting‑edge research and publish results in top AI conferences and journals whenever opportunities arise. Key Requirements PhD degree in Data Science, Computer Science, Information Technology, Artificial Intelligence, Physics or related field. 1–2 years of experience, preferably in a mathematical, engineering, scientific, or technical setting. Relevant experience in knowledge graphs and retrieval systems. Ability to collaborate effectively within a multidisciplinary and multicultural environment. Curiosity, and a proactive, solution‑oriented mindset. Excitement to work in a dynamic and fast‑paced environment; ability to thrive in ambiguity. Technical Skills Proficiency in Python. Understanding of fundamental computer science principles. Solid understanding of machine learning principles and architectures. Fundamentals of statistics. Excellent research and analytical skills. Experience in ontology engineering and semantic modeling. Experience in designing and developing RAG systems. Familiarity with Neo4j. Contributions to research (publications in top‑tier conferences) or open‑source projects. Nice to Have Proven excellence in relevant areas (e.g., awards, competition wins). Proven ability to independently solve complex problems or lead challenging projects. Academic or practical background in physics or other natural sciences/engineering. Experience with good coding practices and software development standards. Proficiency in agentic and deep learning frameworks. Hands‑on experience with large language models and/or other state‑of‑the‑art models. What We Offer Competitive compensation. Stock Options Plan: Empowering you to share in our success and growth. Cutting‑Edge Tools: Access to state‑of‑the‑art tools and collaborative opportunities with leading experts. Work‑Life Balance: Flexible work arrangements in one of our offices with potential options for remote work. Professional Growth: Opportunities to attend industry conferences, present research findings, and engage with the global AI research community. Impact‑Driven Culture: Join a passionate team focused on solving some of the most challenging problems at the intersection of AI and hardware. As set forth in Axiomatic_AI’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. #J-18808-Ljbffr