Staff / Principal Machine Learning Engineer, Serving in Nottingham

Staff / Principal Machine Learning Engineer, Serving in Nottingham

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

  • Tasks: Develop and optimise cutting-edge machine learning models for real-time applications.
  • Company: Join a top AI research lab backed by major investors and industry leaders.
  • Benefits: Competitive salary, equity options, and a supportive work environment.
  • Other info: Dynamic team culture with opportunities for growth and open-source contributions.
  • Why this job: Make a real impact in AI with innovative projects and a flat structure.
  • Qualifications: Experience in machine learning frameworks and high-performance systems.

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 and sub-second multimodal inference at scale 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.
  • Inference Optimization: Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM.
  • Model Acceleration: Hands-on experience with quantization, distillation, caching strategies, continuous batching, paged attention, and speculative decoding.
  • High-Performance Systems: Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs.
  • Distributed Systems: You’re comfortable picking a direction and building the map as you go. You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. 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 engineers who say 'I don't know yet' and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater.

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 Machine Learning Engineer, Serving in Nottingham employer: Inworld AI

Inworld is an exceptional employer for those passionate about AI and machine learning, offering a dynamic work culture that prioritises innovation and impact. With a flat structure and a focus on fast iterations, employees are encouraged to tackle ambiguous challenges and contribute to groundbreaking projects that shape the future of technology. The company provides competitive compensation, equity options, and opportunities for professional growth, making it an ideal place for talented individuals looking to make a meaningful difference in the field.

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Contact Details:

Inworld AI Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff / Principal Machine Learning Engineer, Serving in Nottingham

Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.

Tip Number 2

Show off your projects! Whether it's a GitHub repo or a personal website, make sure to showcase what you've built. This is your chance to demonstrate your skills and passion for machine learning and high-performance systems.

Tip Number 3

Prepare for technical interviews by brushing up on your coding skills and system design knowledge. Practice common algorithms and data structures, and be ready to discuss your thought process when tackling complex problems.

Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage directly with us. Don’t hesitate – get your application in!

We think you need these skills to ace Staff / Principal Machine Learning Engineer, Serving in Nottingham

Inference Optimization
Modern Serving Frameworks
vLLM
TRT-LLM
Model Acceleration
Quantization
Distillation

Some tips for your application 🫡

Show Us Your Passion:When you're writing your application, let your enthusiasm for machine learning and AI shine through. We want to see what excites you about the field and how you've engaged with it in the past. Don't hold back on sharing your projects or experiences that showcase your passion!

Be Authentic:Forget the cookie-cutter templates! We’re looking for genuine individuals who can bring their unique perspectives to the table. Share your journey, the challenges you've faced, and how you've overcome them. Authenticity goes a long way in making your application stand out.

Highlight Your Impact:We love seeing candidates who focus on impact over theory. In your application, emphasise the results of your work—how did your contributions make a difference? Whether it's optimising a system or improving performance, show us the tangible outcomes of your efforts.

Apply Through Our Website:Ready to take the plunge? Make sure to submit your application through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. We can't wait to see what you've got!

How to prepare for a job interview at Inworld AI

Know Your Stuff

Make sure you have a solid grasp of inference optimisation and modern serving frameworks like vLLM or TRT-LLM. Brush up on your hands-on experience with quantisation, distillation, and caching strategies. Being able to discuss these topics confidently will show that you're not just familiar with the theory but can apply it in practice.

Show Your Work

Prepare to showcase what you've built, broken, and understood in your previous roles. Bring examples of projects where you’ve optimised performance or tackled complex problems. This is your chance to demonstrate your bias for impact and how you approach engineering challenges.

Embrace Ambiguity

Inworld values engineers who thrive in unclear situations. Be ready to discuss how you've navigated ambiguity in past projects. Share instances where you’ve taken initiative to clarify problems and design solutions, showing that you can turn uncertainty into actionable plans.

Ask the Right Questions

Don’t hesitate to question existing architectures or decisions during the interview. Show your curiosity and desire to understand the 'why' behind choices made in engineering. This will highlight your critical thinking skills and your commitment to delivering high-performance systems.