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 flexible working arrangements.
- Other info: Dynamic environment with opportunities for rapid career growth.
- Why this job: Join a team shaping the future of AI with real-world applications.
- Qualifications: Experience in machine learning, NLP, or relevant practical projects.
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 Basingstoke 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. With a flat structure and a focus on full-cycle research ownership, employees are empowered to tackle ambiguous challenges 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 Basingstoke
✨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 focus on the end result; share the journey and the lessons 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 gives you a chance to highlight your unique experiences and projects directly related to what we do at Inworld.
We think you need these skills to ace Staff / Principal Research Scientist in Basingstoke
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. We want to see your skills in action, so let your projects do the talking.
Be Authentic:We’re not looking for cookie-cutter applications. Be yourself and let your personality shine through. Share your unique experiences and how they’ve shaped your approach to research and problem-solving.
Focus on Impact:When detailing your experience, highlight the impact of your work rather than just listing tasks. We care about what you achieved and how it contributed to the bigger picture, so make that clear!
Apply Through Our Website:Make sure to apply directly 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 from us!
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 create solutions without a clear roadmap. This will demonstrate your ability to thrive in their fast-paced environment.
✨Ask Insightful Questions
Don’t shy away from asking questions during the interview. Inquire about the challenges they face, the impact of their research, and how they measure success. This shows that you’re not just interested in the role, but also in understanding the mission and context behind their work.