Developer Experience / DevEx
Location: Bristol / London
About Fractile
Fractile was founded in 2022 on the bet that, eventually, the world's most capable AI systems would be limited in their impact by the time taken to produce useful outputs. We bet everything on the logical conclusion: that the only way to truly unlock this latent value, to make speed viable at scale, was to radically re-invent the hardware that we run our frontier AI models on. Ever since, we have been building chips and systems that tackle this problem: how to efficiently generate output at thousands of tokens per second, while handling the complexity and capacity challenges of operating large models at very long contexts.
The workloads that push to the limits of the current frontier are already transformational; it is the technical and economic limits on inference speed that are constraining progress. The defining work of the 21st century will be marked by the engine of inference delivering immense and diffuse chains of intellectual inquiry, in drug discovery, in software engineering, in materials discovery, in any field where progress is driven by deep reasoning and intelligence to resolve complex problems.
The Role
About the Software organisation at Fractile
Developer Experience sits within the Software organisation at Fractile, which is responsible for developing a full software stack for our groundbreaking AI inference systems. That's everything from ML compilers, device drivers and systems firmware, application level runtime and ecosystem integrations, ML and compute libraries, great developer tooling and a full portfolio of simulators, through to datacenter scale workload deployment solutions. At Fractile, we know that a fantastic software stack is a critical and central part of any AI inference solution and it sits at the heart of everything we're doing.
About the team and role
The Developer Experience team at Fractile helps shape how our customers interact with the Fractile inference accelerator. We work across the company to identify, create, and present information on how the system is being used, as well as providing the tooling to help optimise our customers' usage of the system, while keeping a shallow learning curve.
As a member of the Developer Experience team you will need to understand the current state of development for inference hardware. You will need to be able to identify what will work well for engineers wanting to identify potential opportunities for performance improvements, while knowing what tooling will fit into an existing LLM engineer's workflow with the minimal amount of disruption and effort.
About you
We're looking for someone who is self-driven and capable of identifying tooling opportunities, designing those tools, and delivering them in a way which will fit in with an LLM engineer's existing toolset. You will have worked in this area before, possibly as an FDE or at a company that provides inference services using their own models, and have the ability to develop new tools that are designed to be functional and easy to learn and use.
Key Requirements
What We Offer
Fractile is seeking to increase the clock speed of global progress, one chip at a time. We've recently raised $220M from investors including Founders Fund and Accel and our most important work lies ahead. Join us!
Export controls
Our work involves technologies subject to UK, US and other international export control regulations. Certain roles may require additional eligibility checks to ensure compliance with applicable law. We'll be transparent about this throughout the hiring process.
Fractile designs specialized AI inference hardware and systems to speed frontier-model workloads. It builds purpose-built inference chips and a system stack optimized for memory bandwidth during long-token generation to improve throughput and reduce cost versus GPUs. Unlike GPU-centric approaches, it targets memory bandwidth and data movement bottlenecks with chips tailored for long-token generation, delivering efficiency at scale. Its goal is to make large-scale AI inference faster and more economical for research and production workloads.
Company Size
51-200
Company Stage
Series C
Total Funding
$864.1M
Headquarters
London, United Kingdom
Founded
2022
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Sovereignty: Axelera AI wants to equip European AI Factories with Europa, its new chip dedicated to inference. Axelera AI launches Europa, its second generation of chips dedicated to inference. The Dutch startup is now targeting enterprise servers and data centers, with several integrations announced at Dell and Supermicro and deployments planned in AI Factories in Italy and Luxembourg. Published on September 16, 2026 at 1:48 p.m. Until now positioned on edge AI with its Metis chip, Axelera AI is expanding its playing field by launching "Europa", a new architecture intended for more demanding inference uses in enterprises and data centers. Unlike training, inference refers to using an already trained model to produce a result. This chip must run language models, multimodal models, agentic systems, as well as image and video analysis models. It will be offered standalone or integrated into PCIe cards, with the goal of being able to add inference capabilities to existing servers. From Dell and Supermicro servers to European AI Factories. The Dutch company announces that its Europa-based cards are validated in Dell and Supermicro servers. It also lists among its partners HPE, Lenovo, Advantech, and Axiomtek. Dell says for its part that it is working with the company and the Italian integrator E4 on infrastructure intended for "AI Factories" in Italy and Luxembourg. An "AI Factory", a term popularized by the European Commission, is a specialized computing infrastructure, designed to train and run AI models at large scale, where standard cloud is not enough. This is one of the main challenges of the launch: getting Axelera AI's chips into the new computing capacities financed by the European Union. The company claims to have deployed its products at more than 600 customers worldwide, in defense, robotics, security, and commerce. It also reports a sales pipeline of more than $1.5 billion, without detailing the share already contracted. Energy efficiency as the main argument. To differentiate itself, the Dutch company emphasizes the energy efficiency of its solution. According to its own benchmarks, its Edge 232p card based on Europa reaches up to 6 times more tokens per second per watt than the competing platform used as a reference. Axelera is thus targeting uses where models must be run frequently or continuously, and where energy cost becomes an important issue. Raw performance is not always higher: on Qwen3 32B dense, Axelera measures 11 tokens per second, versus 13.2 for the competing platform. The company also highlights the fact that its chips make it possible to run models on the customer's infrastructure rather than in the public cloud, an argument intended for sectors subject to strong confidentiality constraints. The "sovereignty" aspect is also highlighted by the company. However, it does not disclose the location of its technology's manufacturing. The scope of this argument therefore remains to be documented. Already dense competition. Axelera AI nevertheless arrives on an already highly competitive inference market. Nvidia and AMD remain the most visible players in data centers, while a new generation of specialists seeks to offer accelerators dedicated to inference, such as d-Matrix and Cerebras. In Europe, Axelera must also contend with several young startups focused on AI chips, including VSORA and Fractile. Alice Vitard, Journalist at L'Usine Digitale
Carmen Alfonso Rico, VP of business operations at UK AI chip startup Fractile, claims the company has potential to become Britain's first one trillion dollar firm. Rico, who founded VC fund Cocoa Ventures in 2021, joined Fractile in June whilst maintaining her investment role. Fractile, which designs chips for AI inference, is reportedly raising $600m at a $5.6bn valuation and has signed a deal to sell chips to Anthropic. The startup, backed by Accel and Founders Fund, was founded in 2022 by Oxford PhD Walter Goodwin. The company's architecture keeps data directly on chip, which it claims can run large language models up to 100 times faster than existing hardware whilst lowering operational costs by 90%. Fractile's specialised chips are expected to be ready for data centre deployment in 2027.
Fractile in talks to raise $600 million at $6.5 billion valuation as Anthropic deal drives AI chip ambitions. The UK chip startup is reportedly seeking a major valuation increase after securing an initial $250 million supply agreement with Anthropic. Hiring A Wealth Management Advisor Prefer on Google British AI chip startup Fractile is in advanced talks to raise about $600 million at a $6.5 billion pre-money valuation, according to Bloomberg, potentially valuing the company at more than six times its level following its previous financing in May. The proposed financing follows an initial $250 million agreement to supply AI inference chips to Anthropic, with the companies also discussing a potentially larger contract. Fractile's hardware is not expected to be ready for deployment until 2027. Valuation jumps on Anthropic commitment. Fractile raised $220 million in May at a valuation of about $1 billion in a round led by Accel, Founders Fund and Factorial Funds. The latest reported discussions would represent a significant increase in the company's valuation only a few months after that financing, with the proposed $6.5 billion pre-money figure reflecting investor expectations around Fractile's potential position in the AI inference market. Anthropic's initial commitment is not yet translating into active chip shipments. Fractile's hardware remains under development, meaning the customer agreement represents an early commercial signal rather than an established production revenue stream. Implementing Enterprise AI And Machine Learning Tools The potential contract nevertheless gives Fractile an important reference customer as it prepares to bring its first production chips to market. Designing chips for AI inference. Fractile was founded in 2022 by Walter Goodwin while he was a PhD student at the University of Oxford's Robotics Institute. The company's strategy is based on the view that AI inference, rather than model training, could become a major bottleneck as AI applications scale. Fractile is developing chips based on an in-memory computing architecture that places data closer to the transistors performing calculations. The approach is intended to reduce the movement of data between processors and separate memory components. The company has claimed its architecture can deliver substantially higher performance and lower costs than conventional GPU-based systems. Earlier claims suggested large language models could run up to 100 times faster and at one-tenth the cost of existing GPU systems, while more recent investor materials describe the performance advantage more conservatively at 25 times faster and one-tenth the cost. Building a semiconductor alternative to Nvidia. Fractile is entering an increasingly competitive market for AI inference hardware, where startups and established semiconductor companies are seeking alternatives to Nvidia's dominant GPU infrastructure. Integrated Circuits Cerebras raised $1.1 billion at an $8.1 billion valuation in September 2025 before going public in May 2026 at a reported valuation of $56.4 billion. Its market value subsequently moved significantly higher. Etched, which develops complete AI inference systems rather than standalone chips, recently raised $700 million at a $21 billion valuation in a round led by Jane Street, which also became its first paying customer. Groq has also raised capital at a $3.5 billion valuation, with Nvidia among its investors. Against that backdrop, Fractile's proposed $6.5 billion valuation would remain below several later-stage competitors, despite the company being years away from commercial chip deployment. Early backers and commercial opportunity. Before its May Series B, Fractile had raised about $17.5 million in seed funding from investors including Kindred Capital, the NATO Innovation Fund and Oxford Science Enterprises. The startup also received angel investment from former Intel chief executive Pat Gelsinger and Arm veteran Stan Boland. Fractile's technology is being developed primarily for AI inference but could potentially be applied to workloads beyond conversational AI, including drug discovery and materials science. Comparing Small Business Loans The company's ability to turn its architecture into a production-ready chip will be central to its commercial prospects as it moves toward its expected 2027 deployment timeline. If the reported financing closes at the proposed terms, Fractile would join a rapidly expanding group of AI semiconductor companies attracting multibillion-dollar valuations as investors seek exposure to infrastructure beyond the dominant GPU market.
Fractile eyes $6.5B valuation after Anthropic chip deal as UK AI challenger takes aim at Nvidia. August 20, 2026 * Fractile is in talks to raise $600M at a $6.5B valuation, up sixfold from May. * The jump follows a $250M chip deal to supply AI inference hardware to Anthropic. * Chips won't ship until 2027, putting Fractile against rivals Cerebras, Etched and Groq. British chip startup Fractile is in advanced talks to raise around $600 million at a $6.5 billion pre-money valuation, according to Bloomberg, more than six times what it was worth after its last round closed in May. The jump follows an initial $250 million deal to supply AI inference chips to Anthropic, with the two sides discussing a larger contract down the line. From $220M to a potential $6.5B. Fractile raised $220 million in May at a roughly $1 billion valuation, led by Accel, Founders Fund and Factorial Funds, itself already a jump from the $200 million round at a $1 billion valuation Fractile was reportedly sounding out with Accel weeks earlier. Three months on, investors are pricing the company at more than six times that May figure, largely on the strength of one customer commitment. Anthropic's order isn't a live supply line yet. Fractile's hardware isn't expected to be ready for deployment until 2027. But it's an early signal that one of the world's largest AI labs is willing to commit to Fractile's architecture before the company has shipped a single production chip. Fractile was founded in 2022 by Walter Goodwin, then a PhD student at the University of Oxford's Robotics Institute, on the bet that inference speed, not raw training power, would become the industry's real bottleneck. The company's chips use an in-memory compute design, storing data directly beside the transistors doing the calculations rather than shuttling it to separate memory chips - an approach Fractile says can run large language models up to 100 times faster and ten times cheaper than current GPU setups, though more recent investor materials frame the claim more conservatively, at 25 times faster and one-tenth the cost. Fractile raised roughly $17.5 million in seed funding before its Series B, backed early by Kindred Capital, the NATO Innovation Fund and Oxford Science Enterprises, with angel checks from former Intel chief executive Pat Gelsinger and Arm veteran Stan Boland. A crowded field with a much higher bar. Fractile isn't alone chasing Nvidia's inference business, and the market around it has moved even faster than Fractile has. Cerebras, which raised $1.1 billion at an $8.1 billion valuation in September 2025, has since gone public. Its May 2026 IPO valued it at $56.4 billion, and shares have since traded as high as roughly $70 billion to $86 billion. Etched, which builds full AI inference systems rather than standalone chips, raised $700 million at a $21 billion valuation this week in a round led by Jane Street, which also became its first paying customer. Groq closed its own round this month at a $3.5 billion valuation, with Nvidia among the investors. That crowd is a useful context for reading Fractile's number. A $6.5 billion valuation looks aggressive against Fractile's own three-month history, but it's still a fraction of what late-stage and public investors are now paying for inference-chip exposure elsewhere, part of why investors are willing to underwrite Fractile despite two more years before its first chip ships. Goodwin has also pitched Fractile's technology as useful beyond chatbots, including for drug discovery and materials science, giving the company a broader addressable market than conversational AI alone, if the hardware performs as promised once it reaches production.
AI chipmaker Fractile in talks to raise $600m at $6.5bn valuation. The company reached an initial agreement to supply around $250m of its chips to Anthropic. Fractile, a British company developing customised chips for AI applications, is in advanced discussions to secure a pre-money valuation of $6.5bn in its latest fundraising round, reported Bloomberg, citing sources familiar with the matter. The startup expects to raise approximately $600m, although a portion of the funds has been invested at a lesser valuation. The ongoing round is being co-led by Lightspeed Venture Partners and Redpoint Ventures, the people said, with Thrive Capital and Founders Fund also reported as co-leads. Fractile has recently reached an initial agreement to supply around $250m of its chips to Anthropic, with intentions to expand the contract in future, the sources added. The chips are not anticipated to be available for use until 2027. Founded in 2022 by University of Oxford roboticist Walter Goodwin, Fractile is focused on developing systems that improve the efficiency of AI model inference, enabling faster generation of answers and solving of complex problems. The startup claims its technology could be applied in diverse areas beyond chatbots, including AI-powered drug and materials discovery. In May, Fractile closed a $220m funding round, which was led by Founders Fund, Accel, and Factorial Funds, joined by Gigascale, Buckley Ventures, Conviction, 8VC, O1A, Felicis, and other existing investors. Proceeds from the funding were expected to support the accelerated development and release of Fractile's inaugural chips and systems, along with expanding its teams in the UK, US, and Taiwan. In February, the company announced plans to invest £100m over three years in its UK operations, directing funds towards expanding its London and Bristol sites and establishing a new hardware engineering centre in Bristol. Fractile stated that this investment aligns with broader government initiatives to position the UK as a centre for AI and data infrastructure. Give your business an edge with its leading industry insights.