Research Intern (AI)

TL;DR

Research Intern (Probabilistic ML): Contributing to exploratory research on uncertainty quantification, robust design, and surrogate modeling with an accent on probabilistic machine learning and Bayesian computation. Focus on extending methodological foundations for scientific and engineering workflows and developing surrogate models for complex systems.

Location: Must be based in or be able to relocate to Boston (US), Toronto (Canada), or Barcelona (Spain). Hybrid setup: 4 days per week in office, 1 day remote.

Company

hirify.global develops verifiable, interpretable AI systems designed to revolutionize semiconductor and photonic hardware development.

What you will do

• Conduct exploratory research to improve and extend uncertainty quantification (UQ) methodologies.
• Support the development of experimental and robust design approaches for scientific and engineering applications.
• Develop and evaluate surrogate modeling approaches for complex systems.
• Collaborate with researchers to structure isolated, high-value research projects.

Requirements

• Currently pursuing a Master’s or PhD in Applied Mathematics, Computer Science, Physics, or a related field.
• Strong proficiency in Python.
• Strong background in probabilistic machine learning, uncertainty quantification, or Bayesian computation.
• Solid mathematical and analytical skills.
• Must have or be able to obtain work authorization for the US, Canada, or Spain.

Culture & Benefits

• Paid summer internship lasting 10–12 weeks.
• Relocation support including temporary housing and travel expenses.
• Potential for transition into a full-time role upon successful completion.
• Opportunity to collaborate with a global team of engineers and AI specialists on high-stakes scientific hardware development.

Hiring process

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