Company details

HEADCOUNT

25-99

ORG TYPE

Startup

SECTOR

Technology & Digital

WEBSITE

https://www.fractile.ai

About the company

Fractile is a UK AI hardware company designing silicon, systems, and software aimed at running frontier AI model inference faster and cheaper than today’s infrastructure. The public narrative focuses on full-stack co-design, spanning transistor-level work through to cloud inference server logic. Fractile exited stealth with a $15m seed round backed by investors including Kindred Capital, the NATO Innovation Fund, and Oxford Science Enterprises. Hiring is concentrated around London and Bristol across silicon, hardware test, manufacturing operations, and systems software.

Locations and presence

Fractile runs two UK hubs in central London and central Bristol, with roles typically tied to one of those offices. Some roles describe a hybrid pattern with three days per week in the office.

Palpable Score

59.0

/ 100

Fractile is stronger than most deep-tech chip startups on early-career access because at least one core silicon role is explicitly written for 0–3 years and recent graduates. The score is capped because pay transparency is thin in job ads and there’s limited public evidence on early-career progression beyond a small number of employee reviews.

Pillar 1: Early-career access

Score

11.0

/ 20

The company advertises a Verification Engineer role explicitly open to 0–3 years’ experience, including recent graduates.
Fractile’s broader live roles list is dominated by senior, lead, and team-lead posts across hardware and software, which narrows true entry-level volume.
The company offers “reach out directly” recruiting for people who don’t match a posted role, but that is not a substitute for repeat junior hiring lanes like internships or associate titles.

Pillar 2: Hiring fairness and transparency

Score

13.0

/ 20

The company’s Greenhouse listings give detailed role scope and required skills, including concrete toolchains (e.g., SystemVerilog, cocotb, Verilator, Bazel) that help candidates self-select.
Fractile states for at least one engineering role that interviews avoid online algorithmic-style testing while still being highly technical, which sets expectations in plain language.
The company does not publish interview stage maps, timelines, or assessment workload on most postings, so candidates have to infer what the loop looks like.

Pillar 3: Learning and support

Score

13.0

/ 20

The company frames the graduate-leaning verification role around accelerated development through exposure to multiple disciplines (verification, modelling, RTL design, and system architecture).
Fractile’s role descriptions repeatedly emphasise cross-team collaboration and “no silos” working across the stack, which can create frequent feedback loops for early-career engineers.
The company does not publish practical onboarding details like 30/60/90 expectations, mentoring cadence, or a learning budget, so support is hard to validate before joining.

Pillar 4: Pay fairness and stability

Score

12.0

/ 20

The company has credible stability signals through a disclosed seed round and a growing headcount, plus permanent roles across engineering and operations rather than repeated short-term contracts.
Fractile has limited compensation transparency in job ads, with no consistent salary bands or equity terms shown on the Greenhouse pages reviewed.
The company has only a small number of publicly visible salary datapoints on third-party platforms, which limits confidence for early-career candidates benchmarking offers.

Pillar 5: Early-career outcomes

Score

10.0

/ 20

The company has a very small employee review footprint, but the available reviews consistently mention strong engineering peers and positive sentiment on culture and leadership.
Fractile’s public hiring volume and team-size claims suggest growth, but public sources do not show junior-to-mid promotion timelines, intern-to-full-time conversion, or retention over 12–24 months.
The company’s LinkedIn footprint indicates a scaling organisation, but there are not yet enough independently verifiable early-career outcome signals to score this pillar higher.