Interpretability Researcher
Posted yesterday · 0 applicants
Saving, applying or scoring takes a few seconds to set up your free account.
The role in plain words
- Doctoral degree in machine learning, applied mathematics, or a related field
- Experience in interpretability research
- Familiarity with interpretability tools such as Integrated Gradients, SHAP, or attention visualizations
Extracted from the job description · kept up to date automatically
Who this suits
Full job description
Original listing · kept for referenceHome/Careers/Interpretability Researcher
Core AI Research
Interpretability Researcher
Interpretability Researchers develop methods to understand and explain AI decisions.
Apply for this roleManage an applicationBack to careers
Overview
Interpretability Researchers develop methods to understand and explain AI decisions.
Responsibilities
• Plan and run experiments: Design studies to identify how models process information and make predictions.
• Develop tools: Create and maintain open-source interpretability libraries and visualizations.
• Review literature: Stay up-to-date on academic research and synthesize findings into internal reports.
• Perform mathematical research: Investigate inductive biases and underlying principles of neural networks.
• Communicate findings: Write papers, present results, and coordinate with volunteers or collaborators.
Qualifications
• Doctoral degree in machine learning, applied mathematics, or a related field.
• Experience in interpretability research and familiarity with tools such as Integrated Gradients, SHAP, or attention visualizations.
Equal opportunity
TAIRC evaluates candidates using role-related evidence and documented review criteria. Employment decisions must not be based on protected personal characteristics.
Engagement pathways and compensation status
TAIRC is currently building its funding base. Opportunities identified as volunteer or unpaid do not provide compensation at this stage. Any future paid appointment would require available funding, organizational approval, applicable legal compliance, and a separate written agreement. Participation does not guarantee future employment or compensation.
• Volunteer contribution interest may be reviewed only as a voluntary, scoped pathway.
• Educational internship interest requires separate supervision, educational purpose, and legal review.
• Advisory expressions of interest are not board or formal advisory appointments.
• Future compensated employment is contingent on funding, approval, legal compliance, and a separate written offer.
Accessibility and accommodations
For an accommodation or alternate submission format, contact hr@tairc.com. The application form does not request medical documentation or sensitive identity documents.
Posting information
Department Core AI Research
Public role ID TAIRC-ROLE-010
Status Open
Location, employment type, workplace type, compensation, sponsorship policy, posted date, and closing date are omitted unless HR has entered approved factual values.
Recruitment privacy
Application data is used for recruitment review, stored with restricted access, and handled under the recruitment privacy and retention policy.
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- Doctoral degree in machine learning, applied mathematics, or a related field, Experience in interpretability research, Familiarity with interpretability tools such as Integrated Gradients, SHAP, or attention visualizations