Staff / Principal Research Scientist - UK
Staff / Principal Research Scientist - UK

Staff / Principal Research Scientist - UK

Full-Time 140000 - 200000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Tackle complex AI challenges and develop groundbreaking multimodal models.
  • Company: Join a leading AI research lab backed by top investors and industry giants.
  • Benefits: Competitive salary, equity options, and a supportive work environment.
  • Other info: Flat structure, fast iterations, and opportunities for career growth.
  • Why this job: Make a real impact in AI research and innovation with a dynamic team.
  • Qualifications: Experience in machine learning, NLP, or relevant practical projects.

The predicted salary is between 140000 - 200000 £ per year.

About Inworld

Inworld is a product-oriented research lab of top AI researchers and engineers, developing best-in-class realtime multimodal models and the only realtime orchestration platform optimized for thousands of queries per second. We’ve raised more than $125M from Lightspeed, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta and Stanford, among others. Our technology has powered experiences from companies such as NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella and Bible Chat. We’ve also been recognized by CB Insights as one of the 100 most promising AI companies globally and have been named one of LinkedIn's Top 10 Startups in the USA.

Who We're Looking For

A year ago, reliably working agentic systems barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood.

Experience We Find Useful

  • You don't need all of this. But you need enough to make a case.
  • Foundation models: training, new architectures, RL, reward modeling, scaling
  • Evaluation: benchmarks, eval loops, quality measurement, LLM-as-judge, failure analysis
  • Frontier topics: multimodal models, agents, tool use, test-time compute, world models
  • Published research at ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI
  • PhD in ML/NLP — or equivalent practical experience you can point to
  • Public work: non-trivial AI side projects, interdisciplinary experiments, open-source contributions
  • Full-stack research ownership: you frame the question, run the experiments, write the paper, ship the result

If you learned through building, competitions, or collaborations outside academia — that counts. We care about evidence, not credentials.

Who Thrives Here

  • Pathfinders: You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go.
  • Full-Cycle Researchers: You believe research isn't finished until it’s shipped. You have a bias for impact over purely academic output.
  • First-Principles Engineers: You don't just ship code; you obsess over the why. You’re the first to question an approach if you think there’s a better way to solve the core problem.
  • Mission Owners: You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make.

What Working Here Is Like

We hand you unclear problems and expect you to make them clear. We value researchers who say "I don't know yet" — and then design the experiment that finds out. We treat evaluation as a first-class research product, not a box to check before launch. Impact comes before publications though we support sharing work that moves the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater.

We don't need a cover letter. A link to something you've built tells us more.

The base salary range for this full-time position is £140,000 – £200,000. In addition to base pay, total compensation includes equity and benefits. Within the range, individual pay is determined by work location, level, and additional factors, including competencies, experience, and business needs. The base pay range is subject to change and may be modified in the future.

Candidates must already have the legal right to work in the United Kingdom, as visa sponsorship is not available for this role. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements.

Staff / Principal Research Scientist - UK employer: Inworld

Inworld is an exceptional employer for those passionate about AI research, offering a dynamic work culture that encourages innovation and impact over traditional academic output. With a flat structure and a focus on real-world applications, employees are empowered to tackle ambiguous problems and see their work come to life, all while benefiting from competitive compensation and equity options. Located in the UK, Inworld provides a unique opportunity to be part of a leading-edge team recognised globally for its contributions to AI technology.
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Contact Detail:

Inworld Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff / Principal Research Scientist - UK

✨Tip Number 1

Get your hands dirty with projects that showcase your skills. Whether it's a side project or an open-source contribution, having something tangible to show us can really set you apart. We love seeing what you've built and how you've tackled challenges.

✨Tip Number 2

Network like a pro! Reach out to people in the industry, attend meetups, or join online forums. You never know who might have a lead on a role or can give you insider tips about the company culture at places like Inworld.

✨Tip Number 3

When you get that interview, be ready to discuss not just your successes but also your failures. We want to hear about what you've learned from your experiences. It shows resilience and a growth mindset, which we value highly.

✨Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen. Plus, it gives you a chance to tailor your submission to what we’re looking for, making it easier for us to see how you fit into our team.

We think you need these skills to ace Staff / Principal Research Scientist - UK

Foundation Models
Reinforcement Learning (RL)
Reward Modeling
Quality Measurement
Multimodal Models
Evaluation Loops
Failure Analysis
Published Research in AI Conferences
PhD in Machine Learning/Natural Language Processing
Full-Stack Research Ownership
Interdisciplinary Experiments
Open-Source Contributions
Problem Framing
Experiment Design
Impact Orientation

Some tips for your application 🫡

Show Us What You've Built: Forget the traditional cover letter! Instead, share a link to something you've created or contributed to. This gives us a real insight into your skills and creativity.

Be Authentic: We’re not looking for cookie-cutter resumes. Be yourself and let your personality shine through. Highlight your unique experiences and how they’ve shaped your approach to research.

Focus on Impact: When detailing your past work, emphasise the impact of your projects rather than just listing tasks. We want to see how you’ve made a difference and what you’ve learned along the way.

Apply Through Our Website: Make sure to submit your application through our website. It’s the best way for us to keep track of your application and ensures you don’t miss out on any updates!

How to prepare for a job interview at Inworld

✨Know Your Stuff

Make sure you’re well-versed in the latest advancements in AI and machine learning. Brush up on foundation models, evaluation techniques, and any frontier topics mentioned in the job description. Being able to discuss your own projects or research will show that you’re not just a resume but someone who actively engages with the field.

✨Show Your Problem-Solving Skills

Prepare to discuss how you've tackled ambiguous problems in the past. Inworld values pathfinders who can navigate uncertainty, so think of examples where you’ve taken initiative to clarify complex issues and design experiments to find solutions. This will demonstrate your ability to thrive in their dynamic environment.

✨Emphasise Impact Over Theory

Be ready to talk about how your work has made a tangible impact. Inworld prioritises results over academic accolades, so share stories of how your research or projects have led to real-world applications. Highlighting your bias for action will resonate well with their mission-driven culture.

✨Bring Evidence, Not Just Credentials

Since Inworld is looking for evidence of your capabilities rather than just formal qualifications, prepare a portfolio of your work. This could include links to projects, papers, or open-source contributions. Showing what you’ve built and how it relates to the role will set you apart from other candidates.

Staff / Principal Research Scientist - UK
Inworld

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