At a Glance
- Tasks: Build innovative tools for AGI safety research and enhance evaluation processes.
- Company: Join a cutting-edge tech company focused on AI safety and research.
- Benefits: Enjoy competitive salary, unlimited vacation, flexible hours, and professional development budget.
- Other info: Collaborative team culture with excellent growth opportunities and diverse backgrounds welcomed.
- Why this job: Make a real impact in AI safety while working with top researchers and engineers.
- Qualifications: Experience in Python and React; passion for AI and software development.
The predicted salary is between 100000 - 200000 ÂŁ per year.
Application deadline: We are conducting interviews actively and aim to fill this role as soon as we find someone suitable.
ABOUT THE OPPORTUNITY
We’re looking for Full-stack Software Engineers who are excited to build tools for frontier AGI safety research, e.g. building and maintaining evals libraries and tools for monitoring and controlling our own LLM traffic.
REPRESENTATIVE PROJECTS
Your main objective is to develop tooling for analyzing model evaluation results. Here is a list of features that you might build and ship in your first 6 months:
- LLM-powered search that finds interesting fragments in evaluation transcripts
- Comparison views that show how conversations and scores differ between two evaluation runs
- Ability to view and analyse conversations with coding agents (Cursor, Claude Code, etc.) in addition to evaluation transcripts
- Results streaming for evaluations that are currently being run
- Collaborative editing of evaluation logs that automatically updates metrics and other derived data.
Think of this as developing an “IDE for evaluations”. Besides this, here are example auxiliary projects which you might do:
- Automated evaluation pipelines to minimize the time from getting access to a new model for pre-deployment testing to analyzing the most important results and sharing them.
- LLM agents and MCP tools to automate internal software engineering and research tasks, with sandboxes to prevent major failures
- Telemetry API and instrumentation of our existing tools, allowing us to monitor usage and improve reliability
- Upstream improvements to the Inspect framework and ecosystem, e.g. support for evaluating modern agentic scaffolds.
KEY RESPONSIBILITIES
- Balance between moving quickly and creating robust and performant software
- Lead the development of major features from ideation to implementation
- Support the entire user journey from running the evaluation to finding interesting results to analysing the results to producing reports and papers
- Make the software configurable and extensible, so that users can adapt it for their needs
- Collaboratively define and shape the software roadmap and priorities
- Establish and advocate for good software design practices, codebase health, and coding agent practices
- Work closely with researchers to understand what challenges they face
- Work closely with the product team to create solutions that satisfy both our researchers and external customers
KEY REQUIREMENTS
You must have experience writing production-quality Python and React code. We value candidates from diverse backgrounds and recognise that candidates may demonstrate their skills in different ways. For example, we might be impressed if you have:
- Led the development of a successful software tool or product over an extended period (e.g. 1 year or more)
- Started and built the tech stack for a company, e.g in a start-up
- Worked your way up in a large organisation, repeatedly gaining more responsibility and influencing a large part of the codebase
- Authored and/or maintained a popular open-source tool or library
- Placed in a prestigious programming competition (IOI, ICPC, etc.)
- 5+ years of professional software engineering experience
The following would be a bonus:
- Experience designing rich and intuitive UIs, especially for power users
- Direct work with researchers or customers
- Experience working with LLM agents or LLM evaluations
- Interest in AI Safety
We want to emphasize that people who feel they don’t fulfill all of these characteristics but think they would be a good fit for the position nonetheless are strongly encouraged to apply. We believe that excellent candidates can come from a variety of backgrounds and are excited to give you opportunities to shine.
LOGISTICS
- Time Allocation: Full-time
- Location: This is an in-person role working out of our London or San Francisco office.
- Visa sponsorship: We sponsor visas in both the UK and US. Sponsorship isn't guaranteed for every role or candidate, but if we make you an offer, we'll work with you to find the right visa route.
BENEFITS
This role offers market competitive salary, equity, and competitive benefits.
- Salary: 100k - 200k GBP (~135k - 270k USD)
- Flexible work hours and schedule
- Unlimited vacation
- Unlimited sick leave
- Up to 6 months of paid parental leave
- Comprehensive health, dental and vision insurance
- Retirement savings with competitive employer matching (e.g. 401(k) for US employees)
- Lunch, dinner, and snacks are provided for all employees on workdays
- Paid work trips, including staff retreats, business trips, and relevant conferences
- A yearly $1,000 (USD) professional development budget
ABOUT THE TEAM
The SWE team currently consists of Rusheb Shah, Andrei Matveiakin, Alex Kedrik, and Glen Rodgers. Beyond the SWE team, you will closely interact with the research scientists and engineers as the primary user group of your tools.
ABOUT THE APOLLO RESEARCH
The rapid rise in AI capabilities offers tremendous opportunities, but also presents significant risks. At Apollo Research, we’re primarily concerned with risks from Loss of Control, i.e. risks coming from the model itself rather than e.g. humans misusing the AI. We’re particularly concerned with deceptive alignment / scheming, a phenomenon where a model appears to be aligned but is, in fact, misaligned and capable of evading human oversight. We work on the detection of scheming (e.g. building evaluations), the science of scheming (e.g. model organisms), and scheming mitigations (e.g. anti-scheming, and control). We closely work with multiple frontier AI companies, e.g. to test their models before deployment or collaborate on scheming mitigations. At Apollo, we aim for a culture that emphasizes truth-seeking, being goal-oriented, giving and receiving constructive feedback, and being friendly and helpful.
If you’re interested in more details about what it’s like working at Apollo, you can find more information here.
Equality Statement: Apollo Research is an Equal Opportunity Employer. We value diversity and are committed to providing equal opportunities to all, regardless of age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, or sexual orientation.
INTERVIEW PROCESS
Please complete the application form with your CV. The provision of a cover letter is optional but not necessary. Please also feel free to share links to relevant work samples.
About the interview process: Our multi-stage process includes a screening interview, a take-home test (approx. 2 hours), 3 technical interviews, and a final interview with Marius (CEO). The technical interviews will be closely related to tasks the candidate would do on the job. There are no leetcode-style general coding interviews. If you want to prepare for the interviews, we suggest working on hands-on LLM evals projects (e.g. as suggested in our starter guide), such as building LM agent evaluations in Inspect.
Full-stack Software Engineer (Research team) in London employer: Apollo Research
Contact Detail:
Apollo Research Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Full-stack Software Engineer (Research team) in London
✨Tip Number 1
Get your hands dirty with some real projects! Dive into LLM evals or similar tools to showcase your skills. This not only helps you understand the tech but also gives you something solid to talk about in interviews.
✨Tip Number 2
Network like a pro! Connect with folks in the AI safety and software engineering communities. Attend meetups, webinars, or even just reach out on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 3
Prepare for those technical interviews by practising with real-world scenarios. Focus on the kind of problems you'd face in this role, especially around building tools for evaluations. It’ll make you feel more confident and ready to impress!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Apollo Research.
We think you need these skills to ace Full-stack Software Engineer (Research team) in London
Some tips for your application 🫡
Show Your Passion: When you're writing your application, let your enthusiasm for AI safety and software engineering shine through. We want to see that you’re genuinely excited about the opportunity to work on cutting-edge projects that make a difference!
Tailor Your CV: Make sure your CV highlights relevant experience, especially with Python and React. We love seeing how your past projects align with what we do, so don’t be shy about showcasing your achievements and skills that fit the role.
Keep It Clear and Concise: While we appreciate detail, clarity is key! Make your application easy to read and straight to the point. Use bullet points where possible to break down your experience and skills, making it easier for us to see why you’d be a great fit.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team!
How to prepare for a job interview at Apollo Research
✨Know Your Tech Stack
Make sure you’re well-versed in Python and React, as these are crucial for the role. Brush up on your coding skills and be ready to discuss your past projects that involved these technologies.
✨Understand the Research Focus
Familiarise yourself with AGI safety research and the specific challenges it presents. Being able to discuss how your work can contribute to this field will show your genuine interest and alignment with the company's mission.
✨Prepare for Technical Interviews
Since the technical interviews will focus on real tasks, practice hands-on LLM evals projects. This will not only help you get comfortable with the type of work you'll be doing but also give you concrete examples to discuss during the interview.
✨Show Collaborative Spirit
Highlight your experience working closely with researchers or product teams. Emphasise your ability to communicate effectively and advocate for good software design practices, as collaboration is key in this role.