Axiomatic_AI
AI Research Scientist - Formal Methods for Science
Axiomatic_AI, Boston, Massachusetts, us, 02298
AI Research Scientist - Formal Methods for Science
Join to apply for the AI Research Scientist - Formal Methods for Science role at Axiomatic_AI
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). Our mission is to revolutionize the fields of hardware design and simulation in the photonics and semiconductor industry, bringing these innovations from development to commercial product.
Position Overview As an AI Research Scientist focused on formal methods for science, you will join a focused team, playing a key role in building new formal verification tools for science and engineering. Your responsibilities include developing AI tools to enable systematic adoption of formal methods in quantitative scientific fields such as physics and engineering; managing data curation; conducting benchmarking to evaluate performance; analyzing reasoning flaws and proposing solutions. You will collaborate closely with a cross‑functional team of mathematicians, AI engineers, software engineers, Lean4 developers, physicists and AI scientists.
Your Mission
Project contribution and technical execution:
Design and develop autoformalization and validation strategies tailored for scientific applications.
Solution design & implementation:
Hands‑on development to drive short‑term impactful solutions with the Business Development team. Propose, discuss and implement technical solutions that address complex challenges, ensuring they are well‑structured, efficient and aligned with industry best practices.
Innovation & continuous learning:
Stay updated with state‑of‑the‑art techniques and advancements, continuously integrating the latest research to enhance product impact.
Cross‑team collaboration:
Work closely with AI and development teams to ensure seamless integration of solutions, promoting open communication and cooperation to enhance productivity and technical excellence.
Knowledge sharing and team development:
Foster a collaborative culture by sharing knowledge, insights and best practices, encouraging teamwork and continuous learning to strengthen overall expertise within the company.
Key Requirements
PhD in Computer Science, Artificial Intelligence, Physics, Machine Learning for scientific applications or related fields.
Experience in applying machine learning to relevant projects.
Proficient in Python, with ability to write clean and efficient code.
Experience with agentic AI and major deep learning frameworks.
Solid understanding of statistics and probability.
About You
You excel as a team player, thriving in multidisciplinary and multicultural environments.
You are highly motivated, hard‑working and committed to personal and professional growth through continuous learning, new challenges and advancements.
You quickly grasp new concepts and technologies, adapting efficiently to evolving requirements.
You have a real passion for science and maths, and deep curiosity for understanding concepts from first principles.
You like to try new technologies and quickly build exploratory prototypes.
You thrive in a dynamic, fast‑paced environment, embracing change with a proactive and solution‑oriented approach.
Nice to Have
Background in Physics, Engineering or other related computational science.
Publications relevant to the company domain at top‑tier conferences.
Internship or work experience in a top AI company.
Strong experience in at least one of the following: reinforcement learning, representation learning, program synthesis, NLP, graph machine learning, knowledge graphs, applied machine learning and data mining, optimisation, machine learning for theorem proving, agentic LLMs and RAG, machine learning for science.
Proven contribution to open source projects.
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 in artificial intelligence, physics, hardware and electronic design automation.
Work‑Life Balance:
Flexible work arrangements in one of our offices with potential remote work options.
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.
Seniority Level
Entry level
Employment Type
Full‑time
Job Function
Engineering and Information Technology
Industries
Technology, Information and Internet
#J-18808-Ljbffr
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). Our mission is to revolutionize the fields of hardware design and simulation in the photonics and semiconductor industry, bringing these innovations from development to commercial product.
Position Overview As an AI Research Scientist focused on formal methods for science, you will join a focused team, playing a key role in building new formal verification tools for science and engineering. Your responsibilities include developing AI tools to enable systematic adoption of formal methods in quantitative scientific fields such as physics and engineering; managing data curation; conducting benchmarking to evaluate performance; analyzing reasoning flaws and proposing solutions. You will collaborate closely with a cross‑functional team of mathematicians, AI engineers, software engineers, Lean4 developers, physicists and AI scientists.
Your Mission
Project contribution and technical execution:
Design and develop autoformalization and validation strategies tailored for scientific applications.
Solution design & implementation:
Hands‑on development to drive short‑term impactful solutions with the Business Development team. Propose, discuss and implement technical solutions that address complex challenges, ensuring they are well‑structured, efficient and aligned with industry best practices.
Innovation & continuous learning:
Stay updated with state‑of‑the‑art techniques and advancements, continuously integrating the latest research to enhance product impact.
Cross‑team collaboration:
Work closely with AI and development teams to ensure seamless integration of solutions, promoting open communication and cooperation to enhance productivity and technical excellence.
Knowledge sharing and team development:
Foster a collaborative culture by sharing knowledge, insights and best practices, encouraging teamwork and continuous learning to strengthen overall expertise within the company.
Key Requirements
PhD in Computer Science, Artificial Intelligence, Physics, Machine Learning for scientific applications or related fields.
Experience in applying machine learning to relevant projects.
Proficient in Python, with ability to write clean and efficient code.
Experience with agentic AI and major deep learning frameworks.
Solid understanding of statistics and probability.
About You
You excel as a team player, thriving in multidisciplinary and multicultural environments.
You are highly motivated, hard‑working and committed to personal and professional growth through continuous learning, new challenges and advancements.
You quickly grasp new concepts and technologies, adapting efficiently to evolving requirements.
You have a real passion for science and maths, and deep curiosity for understanding concepts from first principles.
You like to try new technologies and quickly build exploratory prototypes.
You thrive in a dynamic, fast‑paced environment, embracing change with a proactive and solution‑oriented approach.
Nice to Have
Background in Physics, Engineering or other related computational science.
Publications relevant to the company domain at top‑tier conferences.
Internship or work experience in a top AI company.
Strong experience in at least one of the following: reinforcement learning, representation learning, program synthesis, NLP, graph machine learning, knowledge graphs, applied machine learning and data mining, optimisation, machine learning for theorem proving, agentic LLMs and RAG, machine learning for science.
Proven contribution to open source projects.
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 in artificial intelligence, physics, hardware and electronic design automation.
Work‑Life Balance:
Flexible work arrangements in one of our offices with potential remote work options.
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.
Seniority Level
Entry level
Employment Type
Full‑time
Job Function
Engineering and Information Technology
Industries
Technology, Information and Internet
#J-18808-Ljbffr