About Us 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.

Our mission, 30×30, is to deliver a 30× improvement in the speed, accessibility, and cost of semiconductor and photonic hardware development by 2030.

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.

Position overview

We are looking for a Research Intern to support exploratory work on core topics in agentic AI and learning systems. The internship is designed around two main goals: identifying promising research paths and producing strong research output, potentially including a paper submission.

You will contribute to exploratory but highly relevant research directions within KAMAS (Knowledge, Agents, Memory and Systems), a team focused on building knowledge-driven, verifiable agentic AI systems. Possible investigation paths include:-

• Teacher/student interaction dynamics in learning processes, particularly in long-term settings where the student evolves through sustained interaction with a teacher;
• The interaction between external and parametric memory, focusing on how to connect them and enable effective bidirectional information flow;
• Neurosymbolic approaches to validation and verification (V&V) for agentic reasoning

These directions are not exhaustive. Additional research paths may be defined based on the candidate’s background, interests, and emerging project needs

This role is ideal for a candidate who enjoys moving between conceptual research, experimental work, and hands-on model development.

Your mission

• Contribute to exploratory research in agentic AI and learning systems, aligned with KAMAS goals and research priorities
• Design, implement, and run experiments to evaluate promising research directions
• Synthesize findings into internal documents and presentations, and potentially publications.

Key Requirements

• Currently pursuing a Master’s or PhD in Artificial Intelligence, Computer Science, Machine Learning, or a related field
• Strong proficiency in Python
• Strong foundation in machine learning research and experimental design
• Ability to work independently on exploratory research problems
• Strong analytical, research, and communication skills
• Strong teamwork and collaboration skills
• Comfort working in a dynamic, fast-paced setting
• Strong interest in current state-of-the-art AI research, in particular in knowledge and memory systems.

Work model & location expectations Work Model

• Primarily on-site. Candidates are expected to be based in one of our offices (Toronto, Boston, or Barcelona), with a hybrid setup of 4 days per week in the office and 1 day remote.
• Primary locations: Toronto, Boston, or Barcelona
• Work authorization: Candidates must have (or be able to obtain) work authorization in one of these locations.
• Relocation support: Axiomatic will support relocation by covering temporary housing and travel to/from the office location during the transition period.

Hiring manager & interview process The Interview Process Consists Of Four Stages

• Culture interview
• Technical + Hiring Manager interview (1 hour)
• Team interview
• Offer stage

Internship details

Type: Paid Summer Internship

Duration: Internships typically run between June and August/September (10–12 weeks), with some flexibility depending on candidate availability and location.

Future Opportunities

• Successful interns may be considered for full-time roles following the internship.

Why join us? At Axiomatic AI, you will be working on technology that drives innovation in AI for scientific and engineering applications in line with our 30×30 mission. This is your opportunity to contribute to the development of new AI methodologies that improve scientific modeling, reasoning, and design. You will work on research questions with both theoretical depth and practical relevance, while collaborating with a global team of engineers, scientists, and AI specialists. We believe in pushing the boundaries of what is possible and continuously seek to redefine the intersection of AI, uncertainty-aware modeling, and scientific computation. If you're excited by technically demanding research and want to help shape the future of AI for engineering and hardware, we want to hear from you.