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 options, and comprehensive benefits package.
- Other info: Dynamic environment with opportunities for rapid career 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 Woking employer: Inworld AI
Inworld is an exceptional employer for those passionate about cutting-edge AI research, offering a dynamic work culture that prioritises innovation and impact over traditional academic metrics. With a flat structure and a focus on fast iterations, employees are empowered to tackle ambiguous problems and see their work come to life, all while enjoying competitive compensation and equity options. Located in the vibrant tech hub of the San Francisco Bay Area, Inworld provides unique opportunities for professional growth and collaboration with industry leaders.
StudySmarter Expert Advice🤫
We think this is how you could land Staff / Principal Research Scientist in Woking
✨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. Building connections can lead to opportunities that aren’t even advertised. Plus, it’s a great way to learn from others and share your own experiences.
✨Tip Number 3
When you get that interview, be ready to discuss your thought process. We want to know how you approach problems and what experiments you've designed. Don’t just tell us what you did; explain why you did it and what you learned along the way.
✨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 Woking
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 these confidently will show that you’re not just a candidate, but a potential contributor.
✨Show Your Work
Bring along examples of your previous projects or research. Whether it’s a paper you’ve published or an open-source contribution, having tangible evidence of your work will speak volumes. This is your chance to showcase your full-cycle research ownership and how you’ve tackled complex problems.
✨Embrace Ambiguity
Inworld values pathfinders who can navigate unclear problems. Be prepared to discuss how you approach ambiguity in your work. Share experiences where you’ve had to design experiments or find solutions without a clear roadmap. This will demonstrate your ability to thrive in their dynamic environment.
✨Ask Insightful Questions
Don’t shy away from asking questions during the interview. Inquire about the challenges the team is currently facing or the direction they see their research heading. This shows that you’re not just interested in the role, but also in understanding the mission and context behind their work.