At a Glance
- Tasks: Lead groundbreaking research in AI voice models and optimise real-time performance.
- Company: Top-ranked AI research lab with a focus on innovation and impact.
- Benefits: Competitive salary, equity, and comprehensive benefits package.
- Other info: Dynamic environment with opportunities for rapid growth and impactful work.
- Why this job: Join a team shaping the future of AI with real-world applications.
- Qualifications: Experience in ML/NLP, strong problem-solving skills, and a passion for research.
The predicted salary is between 140000 - 200000 £ per year.
About Inworld
Inworld is a research lab of top researchers and engineers, building the world’s top-ranked realtime voice models. Today our models are the #1 ranked realtime voice models in the world. They are used to power the largest consumer-facing AI applications available, across categories like health, fitness, learning, therapy, companions, customer experience and media; representing 100s of millions of end users. Our work spans areas like research and development of state-of-the-art models, optimizing realtime inference, and creating best-in-class APIs and products that allow developers to engage their users.
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 in Cardiff employer: Inworld AI
Inworld is an exceptional employer for those passionate about cutting-edge AI research and development. With a flat structure that encourages innovation and rapid iteration, employees are empowered to tackle ambiguous problems and make a tangible impact in the field. The company offers competitive compensation, equity options, and a culture that values visibility and collaboration, making it an ideal environment for growth and meaningful contributions in the vibrant tech landscape of the UK.
StudySmarter Expert Advice🤫
We think this is how you could land Staff / Principal Research Scientist in Cardiff
✨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. Engaging with others can lead to opportunities and insights that you won't find on job boards. Plus, it’s a great way to learn about our culture at Inworld!
✨Tip Number 3
Be ready to discuss your thought process! When we chat, we want to hear how you approach problems and experiments. Don’t just tell us what you did; explain why you did it and what you learned along the way. It shows us you're a true researcher at heart.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows us you’re genuinely interested in being part of our team. So, don’t hesitate—hit that apply button!
We think you need these skills to ace Staff / Principal Research Scientist in Cardiff
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 worked on. This gives us a real insight into your skills and creativity.
Be Authentic:We want to see the real you! Don’t stress about fitting into a specific mould. Share your unique experiences and how they’ve shaped your approach to research and problem-solving.
Focus on Impact:When detailing your past work, highlight the impact it had. We’re all about results, so let us know how your contributions made a difference in your projects or teams.
Apply Through Our Website:Make sure to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Inworld AI
✨Know Your Stuff
Make sure you’re well-versed in the latest advancements in machine learning and natural language processing. Brush up on foundation models, evaluation techniques, and any frontier topics mentioned in the job description. Being able to discuss your understanding of these areas will show that you’re not just a resume but a passionate researcher.
✨Show Your Work
Bring tangible evidence of your past projects, whether they’re published papers or side projects. A link to something you've built can speak volumes about your capabilities. Be ready to discuss what you learned from these experiences, especially if they involved ambiguity or challenges.
✨Embrace the Unknown
Inworld is looking for pathfinders who thrive in uncertainty. Prepare to discuss how you approach unclear problems and turn them into clear research questions. Share examples of times when you didn’t have all the answers but designed experiments to find out more.
✨Understand the Why
Be prepared to dive deep into the reasoning behind your approaches. Inworld values first-principles engineers who question methods and seek better solutions. Think about how you can articulate your thought process and the logic behind your decisions during the interview.