At a Glance
- Tasks: Design and build secure infrastructure for sensitive AI model evaluations.
- Company: Join a cutting-edge research lab making intelligence accessible for everyone.
- Benefits: Top-tier salary, stock options, comprehensive health benefits, and unlimited vacation.
- Other info: Dynamic startup environment with excellent career growth opportunities.
- Why this job: Make a real impact in AI safety while working with innovative technologies.
- Qualifications: Strong Python skills and experience in building secure systems.
The predicted salary is between 70000 - 85000 £ per year.
Our Mission the company is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI.
About the Role
As a Research Software Engineer on the Safety team, you will design, build, and own the infrastructure used to run our most sensitive model evaluations — including evaluations in CBRN (chemical, biological, radiological, and nuclear), child safety, and other dangerous-capability domains. These evaluations inform release decisions for our open models, so the systems you build must be secure, isolated, reproducible, and trustworthy under scrutiny. This is a deeply technical, high-ownership role at the intersection of platform engineering, security, and safety research. You will partner closely with domain experts, legal, and safety researchers to turn their evaluation needs into robust, scalable infrastructure: sandboxed execution environments, controlled data pipelines for sensitive material, access controls, audit logging, and the tooling that lets researchers safely elicit and measure model capabilities in high-consequence areas.
What You'll Do
- Design and build secure, sandboxed infrastructure for running sensitive model evaluations, including CBRN and other dangerous-capability domains.
- Build controlled data pipelines and storage for sensitive evaluation material, applying least-privilege and need-to-know access, role-based access control (RBAC), encryption at rest and in transit, audit logging, and data-minimization safeguards.
- Partner with safety researchers and domain experts to translate evaluation designs into reliable, reproducible, and scalable systems.
- Build eval-orchestration tooling and harnesses that let researchers run high-throughput evaluations against models and agents in isolated environments.
- Develop infrastructure for measuring AI capability uplift in high-consequence domains, and integrate results into the pipelines that inform release decisions.
- Implement guardrails, monitoring, and compartmentalization so sensitive work stays appropriately siloed, applying least-privilege, need-to-know, and defense-in-depth principles across compute, data, and tooling.
- Write production-quality Python (and related tooling) for high-throughput data processing and evaluation systems.
- Improve the reliability, security posture, and developer experience of the safety team's evaluation platform over time.
About You
- Strong software engineering skills, particularly in Python, with a track record of building reliable, scalable infrastructure or platform systems.
- Experience building sandboxed, isolated, or otherwise security-sensitive execution environments (e.g., containerization, VM isolation, secure compute) for Trust and Safety teams.
- Solid grounding in security engineering fundamentals: principle of least privilege, need-to-know access, role-based access control (RBAC), secrets management, encryption, audit logging, compartmentalization, and defense-in-depth design.
- Experience building data pipelines and handling sensitive or restricted data with appropriate safeguards.
- Ability to own entire problems end-to-end, including ambiguous, cross-functional ones.
- Comfort working on sensitive projects that require discretion, integrity, and sound judgment.
- Thrive in a fast-paced, high-agency startup environment with a bias toward action.
Strong candidates may also have
- Experience building evaluation, benchmarking, or experimentation infrastructure for ML systems.
- Experience working with LLMs, agents, or ML training/inference pipelines.
- Familiarity with dangerous-capability or dual-use domains (CBRN, cyber, etc.) and the information-security considerations they involve.
- Familiarity with compliance frameworks relevant to sensitive data handling.
We encourage you to apply even if you don't meet every qualification. Not all strong candidates will match every item listed.
What We Offer:
- Top-tier compensation: Salary and equity structured to recognize and retain our talent globally.
- Stock options: Everyone who joins and contributes to the company's success gets to share in the upside through stock options.
- Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance.
- Meals: Lunch and dinner are provided in the office daily.
- Life & family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys.
- Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K.
- Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable.
- Team building: We have regular off-sites, happy hours, and team celebrations.
Member of Technical Staff - Research Software Engineer - Safety Evaluations Infrastructure employer: United States Digital Space LLC
United States Digital Space LLC is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration in the heart of Greater London. With a strong focus on employee well-being and flexible work options, we provide ample opportunities for professional growth and development, making it an ideal environment for those looking to make a meaningful impact in the field of AI-enabled SaaS engineering.
Contact Details:
United States Digital Space LLC Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Member of Technical Staff - Research Software Engineer - Safety Evaluations Infrastructure
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at United States Digital Space LLC or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to United States Digital Space LLC.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like United States Digital Space LLC.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like United States Digital Space LLC that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Member of Technical Staff - Research Software Engineer - Safety Evaluations Infrastructure
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at United States Digital Space LLC.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at United States Digital Space LLC and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at United States Digital Space LLC
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If United States Digital Space LLC uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.