ML Research Scientist - Member of Technical Staff

1 нед. назад

101k–192k GBP / yearUnited KingdomEuropeLeadOnsite

machine learningpythondeep learning

Research role focused on advancing AI through intelligent systems integrating hardware and software for heterogeneous compute.

О компании

We’re living through a Cambrian explosion of intelligence: new models and new chips, each specialised for different tasks, are arriving all at once. The result is a new era for AI, one of radical heterogeneity.
is the Intelligent Systems Company. We believe the next generation of AI won't be defined by any single model or chip, but by intelligent systems in which hardware and intelligence co-evolve. We are building the infrastructure that unifies heterogeneous compute across the full stack. This opens a new axis of scaling intelligence: a dynamic system that tailors itself to what each workload actually needs, whether that's speed, cost, precision, or whatever unit comes next.
The last era scaled on a different bet: one bigger model, more of the same chip, more data. That bet is running into structural limits. Frontier models offer extraordinary capability at unsustainable cost, one that today's monolithic infrastructure was never designed to serve.
Our founding principle is that intelligence comes from many specialised systems working together, not from any single component. We build the software orchestration layer that co-evolves models, workflows and silicon into one system, delivering inference tailored to every workload, and demonstrating orders-of-magnitude leaps in capability and cost.
Because our software spans the full stack, our engineering team works directly with heterogeneous accelerators and frontier silicon, including Cerebras, d-Matrix, Intel, NVIDIA, AMD, Normal Computing, Tenstorrent, GreatSky, and Mixx. We are not stopping at today's chips: each new generation of silicon unlocks algorithms that couldn't run before, and we intend to be first to them, every time. If we get it right, it will belong to everyone building on it - not to any single vendor.
In our latest funding round, we raised $100M, led by Atomico with participation from Plural, DCVC and the UK Sovereign AI Fund’s first investment. With this, we are building the infrastructure for the next era of intelligence.
We are engineers and scientists based in London, working across the full depth of the stack. We are curious, intellectually honest, and building what doesn't exist yet. If you thrive on uncharted territory and are energised by the scale of the challenge, we'd love to hear from you.

Обязанности

is building a new AI research lab focused on developing the foundations for more capable, efficient, and reliable intelligent systems. We are looking for Research Scientists who can identify fundamental questions, originate new approaches, and turn ambitious ideas into clear empirical results. Our work spans model architectures, learning algorithms, data, reasoning and agents, multimodal systems, evaluation, and efficient training.
Sitting at the heart of our technical mission, this position owns research end to end: from selecting important problems and forming hypotheses to implementing methods, running experiments, and communicating what we learn. You will work with a small, highly technical team and frontier-scale infrastructure, with the autonomy to shape both your research agenda and the lab's broader direction.

Условия

Competitive Salary, determined by skills and experience
Equity & Ownership
Private healthcare
We offer Visa sponsorship and relocation benefits to hire the best in the world
We work in person at our London office. You'll have the tools, space and setup to do your best work, and if you have specific needs, just tell us
We're committed to building an inclusive workplace where everyone feels welcome, and believe in equal opportunities for all.

Другое

Originate and pursue ambitious research directions that can produce fundamental advances in machine learning and intelligent systems
Design, implement, and evaluate novel model architectures, learning algorithms, training methods, data strategies, or agentic systems
Run rigorous experiments from small diagnostic settings through large-scale validation, using results to refine or redirect the research
Build high-quality research code, evaluation harnesses, benchmarks, datasets, and tooling that accelerate scientific progress across the lab
Work across the model, data, and systems stack with research engineers to translate promising ideas into reliable frontier-scale implementations
Communicate findings clearly through internal research reviews and, where appropriate, papers, technical reports, code, and open research artefacts
A PhD or equivalent record of exceptional research and technical achievement, demonstrated through influential publications, spotlights at top-tier conferences, widely used systems or open-source work, or other significant contributions
Deep expertise in at least one relevant area of machine learning, together with strong mathematical and experimental fundamentals
Strong hands-on implementation skills in Python and modern ML frameworks such as PyTorch, with the ability to debug models, experiments, and systems from first principles
The ability to independently own an ambiguous, long-running research agenda while collaborating closely, communicating precisely, and updating quickly from evidence
A track record of originating work that materially influenced a research direction, important system, or technical community
Clear individual ownership of contributions adopted or built upon by strong researchers and practitioners
Experience training, evaluating, or interpreting large-scale foundation models, multimodal systems, or learning agents
Unusually strong research taste, high agency, intellectual honesty, and a low-ego commitment to collective scientific progress