Staff / Principal Machine Learning Engineer, Serving

Inworld AI; United Kingdom; On-site; GBP 140,000 - 200,000; Full time

Job summary

A leading AI research lab is seeking talented individuals to develop sophisticated multimodal models and optimization techniques. The ideal candidate will have a PhD or equivalent experience in CS, Physics, or Math, with proficiency in high-performance systems and distributed scaling solutions. Responsibilities include taking models into production and ensuring performance and reliability across thousands of queries per second. The position offers a base salary of £140,000 – £200,000, along with equity and benefits.

Qualifications

• Deep understanding of modern serving frameworks and optimization techniques.
• Hands-on experience with model quantization and caching strategies.
• Proficiency in performance optimization on NVIDIA GPUs.

Responsibilities

• Work on agentic systems and multimodal inference at scale.
• Take models from the research team and optimize their serving.
• Ensure reliability in production environments.

Skills

Inference Optimization

Model Acceleration

High-Performance Systems

Distributed Systems & Scaling

Public work

Full-cycle ownership

Background in CS, Physics, Math

Education

PhD in CS, Physics, Math or equivalent experience

Tools

C++

CUDA

Rust

Python

Kubernetes

Ray

Job description

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 & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections.
• Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups.
• Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production.
• Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems.

Who Thrives Here

• You don’t need a roadmap to start walking; 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.