About Resolution

Resolution does research on how to align artificial superintelligence (ASI). ASI may be developed in the next few years, but it is unclear whether alignment is on track to be ready in the same timeframe. We aim at higher a priori confidence in aligned outcomes by pursuing a portfolio of theory and empirics bets, any one of which — if it succeeds — would meaningfully advance the field. We invest heavily in research automation to accelerate progress, and we believe that stronger alignment theory unlocks higher automation: more principled approaches give us better filters for which directions of automated research are promising.

Resolution was founded in May 2026 by researchers from UK AISI's Alignment Team, who ran the £30m Alignment Project, and Timaeus, who pioneered applying singular learning theory to alignment.

For more information, see our announcement.

Research at Resolution

We work across a portfolio of research areas, currently including:

Scalable oversight: empirical work on protocols (debate, recursive reward modeling, prover-verifier games) that allow weaker overseers to supervise stronger systems, paired with complexity-theoretic work on equilibria and reachability.
Complexity theory: theoretical work on modeling the interaction of superintelligent agents with lower complexity training environments, including applications to scalable oversight, heuristic arguments, and other agendas.
Learning theory: singular learning theory and its applications, deep learning theory, computational mechanics, etc.
Personas: theory and empirics of low-dimensional structure within model behavior across training and token dimensions.

The full set of bets has not yet been finalized but, in the future, may include further agendas like:

Heuristic arguments: mechanistic understanding of what models know, low-probability estimation.
Game theory: mechanism design, agent foundations, open-source game theory.

A cross-cutting focus is research automation: building infrastructure and tooling to scale all of the above by leveraging AI research assistants at every level of the stack, across both theoretical and empirical work.

About the Role

Research Engineers at Resolution are core members of our research teams, directly driving both research and the core infrastructure behind it. We believe clean engineering on automation, experimentation, and infra is essential to ambitious research, and that excellence on this front requires active research participation.

We're hiring Research Engineers across several main focus areas. We expect the boundaries between these areas to be flexible, but please indicate which mode you're more interested in (or "either") in your application.

Research Automation (primary focus). A cross-cutting function that builds the infrastructure and tooling our researchers use to scale their work, increasingly leveraging fleets of AI research assistants alongside small teams of humans.

Program-embedded Research Engineering (also hiring). Research engineers embedded within one of our research programs (scalable oversight, complexity theory, learning theory, personas, and possible future programs like heuristic arguments or game theory), partnering with researchers on scaling experiments, building program-specific infrastructure, and translating theoretical insights into empirical tools.

Responsibilities

(Research automation track) Build agentic research infrastructure: experiment orchestration, hypothesis generation, automated analysis pipelines; autoformalization tooling for the theory side; internal AI-powered tools for researchers
(Program-embedded track) Scale program experiments to frontier-tier models; build program-specific infrastructure; partner with researchers on engineering and implementation.
(Both) Maintain and extend distributed training, experiment, and evaluation infrastructure
(Both) Contribute to and maintain shared codebases across the org
(Both) Communication of engineering & automation progress, obstacles & learnings to your team and the wider org via Slack and in weekly meetings.

We're on the lookout for excellence, so if you're a cracked engineer who doesn't precisely fit these descriptions, please still apply!

You May Be a Good Fit If You

Have a strong software engineering background, including production-quality Python
Have deep experience with ML frameworks (PyTorch or Jax) and distributed-training stacks
Have a demonstrated ability to ship complex systems end-to-end
Have a Bachelor's degree or equivalent in CS, physics, math, ML, or related
Are willing to use AI tools aggressively in your own workflow, with appropriate care to not get fooled!
Are motivated by alignment of artificial superintelligence (ASI) and want to contribute to it full-time.

Strong Candidates May Also Have

Experience with autoformalization, Lean, or other proof-assistant tooling
Background in research infrastructure or ML platform engineering at frontier labs
Experience scaling ML systems to 100B+ parameter scale
Experience with CUDA kernel development or GPU optimization
Familiarity with alignment research

Other Roles to Consider

If you lean more toward framing and investigating the research questions themselves — designing protocols, proving, conjecturing — than building the systems around them, see Research Scientist. If hardening the automated-research stack sounds like the best part of the job, we have two security seats in the same problem space: Security Engineer (Research Infrastructure) secures the pipeline you'd otherwise be building (CI/CD, agent sandboxing, supply-chain provenance, multi-cloud compute) while Security Engineer (Corporate IT) owns the endpoint, identity, and collaboration layer the whole org runs on.

Application Process

Intro chat. <20-minute conversation to understand your background, motivations, and ideas, and to answer questions you may have about logistics.
Take-home assessment(s). 4-8 hours across 1-2 assessments that simulate working as a Research Engineer at Resolution. We find that assessments like these provide some of the strongest evidence about future performance, and so we truly appreciate your time in completing these tasks. We’ll compensate you for your time, subject to right-to-work constraints. The exact format of the assessments is liable to change, but may involve some but not all of the following:
1. (~4h) Designing and running experiments in response to a narrower research prompt.
2. (~4h) Designing and implementing infrastructure in response to an engineering prompt.
3. (~1h) Solving technical coding problems via a platform like CodeSignal. We have not yet decided whether to conduct coding examinations, but if we do, it would only be for more engineering-heavy roles.
Interview on take-home assessments. We’ll typically follow up assessments with a 45-minute interview to explore how you work through new problems.
Final interview. Interview on your career history, accomplishments, and skills with a senior researcher in our organization.
Work trial. 2-5 days working with us on real problems to assess mutual fit.

Reference checks. Towards the very end of this process, we will, in parallel, reach out for references from past employers.

Timeline. We’re trying to run this process quickly. Our target is a ~1.5-month turnaround from submission to offer. This will mean approximately one week per stage (with the exception of the take-home assessments, which will span 2–3 weeks). Some stages may end up running in parallel. To speed this up further, we will also fast-track exceptional candidates, for instance, by skipping the assessment stage or work trial.

Logistics

Salary: Your salary depends on the scope, autonomy, and impact we expect you to have at Resolution. The expected range of in-person salaries for this role is:

L3 (SWE I): $236,000
L4 (SWE II): $346,000
L5 (Senior SWE): $451,000
L6 (Staff SWE): $670,000
L7 (Senior Staff SWE): $930,000

Strong early-career research engineers will typically come in at L3. Someone with several years of relevant experience would likely start at L4 or L5.

Location: Berkeley, California is strongly preferred; London is a secondary hub; remote may be considered in exceptional cases.

Benefits:

5 weeks of paid vacation per year, in addition to public holidays.
Comprehensive healthcare insurance (medical, dental, vision).
Unlimited sick leave to prioritize your well-being.
An unconditional 401(k) contribution equal to 4% of your salary

Visa sponsorship: We can sponsor visas for relocation to Berkeley.

Minimum education: A bachelor's degree in a field relevant to the role, or an equivalent combination of education, training, and/or professional experience that demonstrates comparable knowledge.

Deadline: Applications are rolling — we'll respond within one week of receipt.

Start date: ASAP.

Research Engineer