Research Scientist

AISafety; Greater London; Híbrido; GBP 93.000 - 126.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Unlimited PTO

Flexible working hours

High ownership & autonomy

Contractor option

Annual health budget

Team meetups

Descripción de la vacante

PrincInt is hiring Research Scientists to work on Ambitious Mechanistic Interpretability (AMI) with fully remote setup. Preference for time spent in London or Bay Area; visa sponsorship available for London/Berkeley candidates.

Start date January 2027, salary USD 125k–170k gross annually. The role focuses on building data models inspired by physics, quantifying data structure relationships, and developing synthetic datasets to benchmark interpretability tools, with mentorship of junior

Formación

• PhD or equivalent research experience in math/physics/ML/CS/neuroscience/complexity.
• Strong ability to communicate complex ideas to technical and non-technical audiences.
• Hands-on training with neural networks and deep learning.
• Experience with scientific computing in Python.
• Comfort with fully remote work.
• Motivation to contribute to AI safety.

Responsabilidades

• Develop tractable data models inspired by statistical physics.
• Quantify the relationship between data structure and learned features.
• Develop synthetic datasets to benchmark interpretability tools.
• Own projects end-to-end and mentor junior researchers.

Conocimientos

Neural networks

Python

Remote work

Communication

Physics/Math background

Educación

PhD or equivalent research experience in math/physics/ML/CS/neuroscience/complexity

Descripción del empleo

We’re hiring Research Scientists to work on Ambitious Mechanistic Interpretability (AMI) at Principles of Intelligence: developing tractable and realistic data structure models, quantifying how the features that AI systems learn are rooted in data, and developing synthetic datasets to benchmark and improve interpretability tools. Fully remote. Strong motivation to work in AI Safety required.

Location: Remote. Strong preference for candidates based in or able to spend significant time in London (UK) and/or the Bay Area (US).

Visa / Work authorization: We can provide visa sponsorship for candidates based in (or relocating to) London (UK) and Berkeley / Bay Area (US), depending on candidate circumstances and role fit.

Type: Full-time.

Start date: January 2027.

Salary range: $125,000–$170,000 USD gross per year, set by seniority and location.

Core Responsibilities

We are hiring for Research Scientists to work on Ambitious Mechanistic Interpretability at PrincInt. The work is aimed at building and advancing methods to:

• Develop tractable data models inspired by statistical physics that capture key aspects of natural data.
• Quantify the relationship between data structure & learned features.
• Develop synthetic datasets to benchmark & improve interpretability tools.

The team is currently focused on exploring a data model based on high-dimensional percolation theory which encodes a statistically self-similar and sparse structure. You’ll help shape the team’s research direction, own projects end to end, and mentor junior researchers and fellows.

This role is fully remote, so we’re looking for people who can thrive in an async environment and are genuinely excited to work on AI safety.

Requirements

We’re looking for a research scientist to lead research projects at the intersection of physics and mechanistic interpretability. You’ll work with a small team conducting interdisciplinary research on synthetic data models, bridging the gap between theories of learning and practical AI interpretability tools. Strong candidates are motivated to contribute to AI safety and can collaborate effectively in a fully remote environment.

Research Scientist

• Must have
  • PhD or equivalent research experience in a technical field such as math, physics, machine learning, neuroscience, computer science, or complexity science
  • Ability to communicate complex, novel ideas to technical and non-technical audiences
  • Working knowledge of neural networks and deep learning, including hands-on model training
  • Experience with scientific computing in Python
  • Comfort working in a fully remote environment
  • Strong motivation to contribute to AI safety
• Great to have
  • A history of publications in ML or another quantitative field demonstrating a track record of original, impactful contributions
  • Experience with mechanistic interpretability research engineering, e.g. linear probing, steering, activation/path patching, SAEs/transcoders
  • Experience defining and leading a research agenda, including mentoring students or junior researchers
  • Working knowledge of statistical physics, especially percolation theory and renormalization; stochastic processes, especially coalescent processes; combinatorics; or network science
  • Hands-on experience with fractal geometry; neural scaling laws (theoretical or empirical); graph and tree algorithms; or representations and theories of concepts in cognitive science

We don’t expect anyone to cover every field above.

Benefits and Salary

Your starting salary range depends on role, prior experience, and location. Our range for this role is $125,000–$170,000 USD gross per year.

Our benefits include:

• Time off: Unlimited PTO, plus two office-wide two-week closures (one in summer, one in winter).
• Flexible working hours: Flexible working hours with an emphasis on outcomes and reliable coordination with teammates.
• High ownership & autonomy: A high-trust environment where you’ll own your work end-to-end, with meaningful responsibility and room to improve systems.
• Employment type: We’re open to either full employment or a contractor arrangement, depending on location and candidate preference.
• Annual budget: $6,000 per year for health benefits, coworking, office equipment or professional development. Work-related travel, conference and publication costs are covered separately.
• Team meetups: We get together in person 2-4 times a year for focused work time, great conversations, and the kind of momentum you only get when the whole team is in the same room.

Diversity and Inclusion

We’re aware that factors like gender, race, and socioeconomic background can affect people’s willingness to apply for roles for which they meet some, but not all, of the suggested attributes. We’d especially like to encourage people from underrepresented backgrounds to express interest.

There’s no such thing as a “perfect” candidate.

If you require any adjustments to the application process, such as accessibility accommodations, additional preparation time, or other, please contact [e-mail] . We’re happy to support your needs and adjust the application process.