software engineer

ai engineer

senior software engineer

full stack engineer

lead software engineer

founder and chief technical officer

Voxquill

<div>I'm looking for our founding engineer!
 
The person who takes a live, paying fintech product and makes it truly ours.
We build receipt-and-proof automation for the self-employed: the app quietly finds your receipts (email, bank feeds, camera roll, texts), sorts them, matches them to your bank transactions, and produces accountant-ready exports. It's live on iOS and Android, it's SOC 2 certified, and people are paying for it. The model works.
I need one person who treats this codebase as theirs, ships fast, and owns the platform end-to-end. This is a founding engineer role with a real path to CTO.
Your first job is to take the keys.
 
Move the platform off the agency's Azure into ours, take custody of production, and the headline deliverable.
 
Build the automated test suite this codebase never had, with a CI/CD pipeline where a green build genuinely means &quot;safe to ship.&quot; Then you own the roadmap.
How we build matters as much as what we build.
 
We are not rebuilding an IT shop of tickets and manual QA.
 
Terrapin runs as an AI-native pod: Claude Code and agents do the repetitive work and produce tested, PR-ready changes; you own architecture, review, security, and the hard 20%.
 
AI gives you the velocity, your tests and pipeline are what keep that velocity from turning into breakage!
We want to ship multiple times a week and almost never break anything, and hold our SOC 2 line the whole way. If that model excites you rather than worries you, you're the person.
This is genuinely full-stack.
 
Strong .NET / C# backend on Azure, real ownership of infra, security, and DevOps, and polished mobile (React Native + Expo, iOS and Android); Because the app is the product. Testing isn't someone else's job here. It's the core discipline.
The kind of person whose teammates would describe as:<ul><li>
an owner, not a ticket-taker</li><li>
obsessive about shipping quality fast</li><li>
calm owning production for a product with real money moving through it</li><li>
someone who builds automation instead of doing the same thing twice</li><li>
security-minded by instinct, not as an afterthought</li></ul>
What you'd bring:<ul><li>
Senior+ .NET / C# backend, PostgreSQL, solid API design</li><li>
Real Azure ownership: App Services, networking, Key Vault, identity, CI/CD (Azure DevOps or similar)</li><li>
Strong React Native + Expo mobile, with genuine UI/UX taste</li><li>
Test automation and CI/CD as a way of life &mdash; you write the tests with the code</li><li>
Hands-on building with Claude Code / agent tooling, and doing it safely in a SOC 2 world</li></ul>
Bonus points: fintech / payments background, Plaid experience, or applied LLM work.
And the reason the right engineer will actually stay: receipts are just the wedge. We're building toward a verifiable, tamper-evident record of an economic event. Proof that banks, insurers, and AI agents can consume directly. Stripe is a payment rails. We're building proof rails.
You'd work directly with me every day &mdash; 18+ years in fintech and payments, two exits behind me &mdash; so you own the engineering but never carry the hard architecture, security, or product calls alone.
The details:
 
UK or EU-remote(temporarily), with solid overlap to UK hours and business trips.
We're genuinely open to strong candidates across both. Being open to relocating to the UK down the line is a plus, but not a day-one requirement.
 
Competitive base plus real founding-level equity.
One hard line: you build quality in through tests and CI/CD. We're deliberately leaving the manual-testing, hope-it-works world behind, and a dev who treats testing as optional isn't the hire. Everything else, we can talk about.
If you want founder-level ownership, a CTO trajectory, and an AI-native way of building, and owning a live fintech platform from week one lights you up, let's talk.
Apply and tell me about something you shipped that you're proud of, and one thing you broke and how you made sure it never happened again.</div>

Founding Engineer (Full Stack); Patch to CTO

White Circle

<div><h1 class="jobSectionHeader">About White Circle</h1>
White Circle is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies &ndash; simple natural-language rules that define what an AI model should and shouldn&rsquo;t do. We automatically test, enforce, and continuously improve these policies at scale.<ul><li>
We&rsquo;ve raised $11M from top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others</li><li>
We process over 100M+ API calls every month</li><li>
We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model</li></ul>
We&rsquo;re at a multi-million dollar run rate already having signed customers like Lovable and multiple neobanks. You&rsquo;ll be joining at the most exciting time - early enough that the equity can be life changing but at a point where demand has been proven.
 
 
We&rsquo;re a small, highly focused team. If you want to work deeply on hard problems and build the category-defining company in AI safety - this role is for you!<h2 class="jobSectionHeader"> 
What You&rsquo;ll Do</h2>
Automate low-value work out of the commercial process so the Sales team can spend more time closing deals<ul><li>
Design and build the systems that power the how we find acquire, and retain customers (both outbound and inbound)</li><li>
Own the CRM: you make sure our data is clean, structured, and reliable</li><li>
Build internal tools, API integrations, and custom automation logic</li><li>
Have real ownership &amp; shape the playbook: what we build, use, how it fits together, and how it scales</li><li>
Design and deploy AI agents across the GTM motion (e.g., account research, pre-call intelligence, personalised outreach etc)</li><li>
Wire it directly into our operational systems so it changes how the team works</li><li>
Design the GTM data model (accounts, contacts and opportunities)</li><li>
Build and manage data pipeline, enrichment and integrations across the stack</li><li>
Build, ship and iterate fast</li></ul><h2 class="jobSectionHeader">
What We&rsquo;re Looking For</h2>
Background &amp; Experience<ul><li>
2+ years of experience in GTM engineering, technical RevOps, or a growth role where you were building automations and pipelines</li><li>
Experience designing and scaling systems in a high-growth company</li><li>
Hands-on with modern GTM tooling - Claude Code, Clay, Apollo, Instantly, n8n or similar - you've built multi-step enrichment and sequencing workflows, not just set up a table</li><li>
Comfortable with Python or SQL well enough to work with data, call APIs, and build lightweight scoring or enrichment logic</li><li>
Top-of-funnel focused - you know how to build systems that generate qualified pipeline at scale, from ICP definition through to booked meetings</li><li>
Experience in programmatic SEO and AEO</li><li>
Analytical and experimental mindset: proven ability to design tests, measure impact, and iterate quickly.</li><li>
Proven AI deployment experience (e.g., automations, agents, workflows)</li></ul><h2 class="jobSectionHeader">
What success looks like in the first 6 months</h2>
In your first six months, we would expect you to identify the highest-converting early segments, build a functioning outbound and follow-up engine, create clear messaging for one or two strong wedges, generate a meaningful pipeline of qualified conversations, and help convert early pilots or customers. Just as importantly, we would expect the company to understand its GTM motion far better because of your work.<h1 class="jobSectionHeader">
Compensation &amp; Benefits</h1><ul><li>
&pound;80k-&pound;110k salary</li><li>
Meaningful equity package</li><li>
All the hardware, tools, and services you need</li><li>
Team off-sites twice a year: we&rsquo;ve recently been to the Alps and to Saint-Tropez</li></ul><h1 class="jobSectionHeader">
How we hire</h1><ul><li>
Intro call with HR</li><li>
Take-home exercise</li><li>
Interview with Head of Revenue</li><li>
Final call with our CEO</li></ul>
Compensation Range: &pound;80K - &pound;100K</div>

Founding GTM Engineer

Understanding Recruitment

<div>
 
 
 Founding MLOps &amp; Data Engineer - London (4 days on site)
 
 
 
 
 
 
 A venture-backed AI startup that's using machine learning to solve one of the biggest challenges in the mining industry are looking for a Founding MLOps &amp; Data Engineer to build the infrastructure that takes cutting-edge ML into production.
 
 
 
 
 
 
 What will I be doing?
 
 
 
 
 
 <ul>
 <li>
 Own the company's MLOps and data engineering strategy from the ground up.
 </li>
 <li>
 Build scalable data pipelines and production ML infrastructure.
 </li>
 <li>
 Develop reproducible, versioned and auditable machine learning workflows.
 </li>
 <li>
 Work closely with ML researchers to productionise new models.
 </li>
 <li>
 Collaborate with product engineers to integrate ML into customer-facing applications.
 </li>
 <li>
 Shape the architecture of the ML platform as the company grows, with plenty of autonomy to influence technical decisions.
 </li>
 </ul>
 
 
 
 
 
 What we're looking for:
 
 
 
 
 
 <ul>
 <li>
 Strong Python engineering skills with experience building production data pipelines.
 </li>
 <li>
 Commercial experience owning MLOps infrastructure and deploying machine learning models.
 </li>
 <li>
 Experience working with cloud platforms (Azure, AWS or GCP).
 </li>
 <li>
 A self-starter who enjoys working in fast-paced startup environments with lots of ownership.
 </li>
 <li>
 Someone who can work through ambiguity, prioritise effectively and solve problems independently
 </li>
 <li>
 Geospatial ML or scientific computing experience would be a plus
 </li>
 <li>
 Experience working in an early-stage or founding engineering team.
 </li>
 </ul>
 
 
 
 
 
 What's in it for you?
 
 
 
 
 
 <ul>
 <li>
 Salary between &pound;70,000 - &pound;100,000 depending on experience.
 </li>
 <li>
 Meaningful equity in a well-funded, early-stage startup.
 </li>
 <li>
 The opportunity to build and own the company's ML platform from day one.
 </li>
 <li>
 Work alongside experienced founders and engineers tackling genuinely difficult technical problems.
 </li>
 </ul>
 
 
 
 
 Apply now for immediate consideration!
 
</div>

Founding MLOps & Data Engineer

Oho Group

<div>
 
 
 Founding AI Engineer | Early Stage AI Start-Up | London
 
 
 
 
 
 
 Founding AI Engineer required to join an extremely well funded, rapidly growing early-stage AI start-up with a world class founding team using AI to solve a real world problem. You&rsquo;ll be one of the first technical hires, working directly with the founders to design, build, and deploy LLM-powered systems that meaningfully shape the product and the company.
 
 
 
 
 
 
 You are:
 
 
 <ul>
 <li>
 2-6 years of professional experience, with strong software engineering fundamentals
 </li>
 <li>
 Proven hands-on experience building AI systems from scratch and deploying LLMs in production
 </li>
 <li>
 Proficiency in Python
 </li>
 <li>
 Academic Excellence: BSc, MSc or PhD in Computer Science, AI, Machine Learning, or related stem field from a top university
 </li>
 <li>
 Comfortable in chaos and thrive in fast paced environments
 </li>
 </ul>
 
 
 
 
 
 Bonus points:
 
 
 <ul>
 <li>
 Experience as an early employee at a start-up
 </li>
 <li>
 Experience working closely with product or founders
 </li>
 </ul>
 
 
 
 
 
 Why join?
 
 
 <ul>
 <li>
 Extremely competitive salary, meaningful equity, and benefits
 </li>
 <li>
 A genuine founding role with significant technical and product ownership
 </li>
 <li>
 Close collaboration with experienced, second-time founders who deeply understand the problem space
 </li>
 <li>
 Strong financial backing from top-tier investors
 </li>
 <li>
 The chance to help shape both the technology and culture from the ground up
 </li>
 </ul>
 
 
 
 
 Looking to join early, play a key role, and build AI systems that solve real-world problems? Let&rsquo;s chat.
 
 
 
 
 
 
 Founding AI Engineer | Early Stage AI Start-Up | London
 
 
</div>

Founding AI Engineer | Early Stage AI Start-Up | London

Substrate Bio

<div><h1 class="jobSectionHeader">The opportunity</h1>
The researchers, data scientists, and ML engineers driving AI-driven biological discovery do not yet know Substrate exists. The Community Manager is the person who will change that.
This is Substrate's first dedicated community hire. You will build from scratch: the relationships, the channels, the content, the events, and the feedback loops that turn a network of interested researchers into an active, technically engaged community. You will be the external face of Substrate to the AI x biology research world, and the voice of that world inside Substrate.<h1 class="jobSectionHeader">
About Substrate</h1>
Substrate is building and operating a network of fully autonomous wet laboratories. We are the critical infrastructure layer for AI-driven biological discovery: cloud-based data production facilities, tightly integrated with AI foundation models, that make high-quality experimental biology as accessible as compute.
We are a small team, four co-founders and a founding hire class now building out, with venture funding and government grants, opening our first node in London and a second node in San Francisco in parallel. The work is hard and the timeline is compressed. We have two scientific verticals live (protein characterisation and functional genomics), a software platform that connects API calls to automated assay execution, and a commercial pipeline that spans foundation model labs, AI biotechs, pharmaceutical companies, and publicly funded research organisations. We are growing to roughly thirty people by early 2027.<h1 class="jobSectionHeader">
The role</h1>
You will own Substrate's community function end to end. The immediate priority is establishing Substrate's presence in the communities where our most important potential users and customers already spend time: AI-biology conferences, academic research groups, frontier AI lab developer communities, and the broader open-science data ecosystem.
The obvious operational pieces are real and important: building and managing Substrate's community channels, creating content (technical posts, case studies, event recaps) that demonstrates what the platform can do, representing Substrate at conferences and research events, and tracking engagement in ways that help the commercial, product and science teams make decisions.
Two parts of the role are less standard, and they are why this hire matters so much to Substrate's success.
The first is technical credibility. Substrate's community spans researchers who publish in leading journals and engineers who build training pipelines for frontier models. Community management here is not event coordination and social media scheduling; it is substantive engagement with people who will interrogate the science, the data quality, and the integration architecture. The Community Manager needs to be able to meet them there.
The second is commercial adjacency. Community at Substrate is not a brand exercise. The relationships built through community will directly feed the commercial pipeline, inform pricing and product decisions, and define which customer segments Substrate chooses to serve deeply. You will work closely with Anna, co-founder, who leads partnerships and go-to-market, and you will operate as a genuine commercial, product and science partner.<h1 class="jobSectionHeader">
What you will do in your first twelve months</h1><h2 class="jobSectionHeader">
FIRST 90 DAYS JUL TO SEP 2026</h2><ul><li>
Map the existing relationships the founding team holds across research institutions, frontier AI labs, pharma and Ai-native biotechs, and the AI-biotech community; understand which are most relevant to a community-first strategy.</li><li>
Establish Substrate's presence on the channels where the AI x biology research community spends time: a newsletter, relevant online communities, forums, podcasts, and a cadence for conference participation.</li><li>
Publish Substrate's first substantive technical community content: a post or article that demonstrates what the platform does and why it matters to researchers doing AI-driven biology.</li><li>
Identify the ten to fifteen research groups, labs, or organisations that should be</li><li>
Substrate's first community anchor relationships, and begin active outreach and relationship building.</li></ul><h2 class="jobSectionHeader">
MONTHS 4 TO 8 OCT 2026 TO FEB 2027</h2><ul><li>
Build and manage an active community presence around the London node opening: coordinate the launch event, manage researcher outreach, and produce the content that captures what Substrate's first operational period looks like.</li><li>
Establish a structured feedback loop between the community and the product and science teams, so that what researchers ask for and struggle with reaches the people who can act on it.</li><li>
Build the San Francisco community presence in parallel: identify the key organisations, events, and channels in the Bay Area AI-biology ecosystem and establish Substrate's footprint there.</li><li>
Develop a content calendar and production cadence that does not depend on the founding team's time to sustain.</li><li>
Refine the community infrastructure: channel selection, moderation policy, engagement metrics, and reporting to the commercial and product teams.</li></ul><h2 class="jobSectionHeader">
MONTHS 9 TO 12 MAR TO JUN 2027</h2><ul><li>
Build the community to a size and engagement level where it is a measurable input to commercial pipeline: researcher referrals, inbound interest driven by community content, and a clear record of which community relationships have become or are likely to become commercial relationships.</li><li>
Produce a community playbook that documents the channels, content types, event formats, and relationship cadences that work for Substrate's audience.</li><li>
Continue building the community infrastructure needed for the San Francisco node: what an active and engaged community looks like in the Bay Area.</li></ul><h1 class="jobSectionHeader">
Who you are</h1>
The pattern we are looking for combines genuine scientific credibility with commercial experience at a technical company. You will have spent five or more years close to research communities, in a developer relations, scientific outreach, partnerships, or community role at an AI, tech or biotech company. You understand how researchers and data scientists think, what they find credible, and how to earn their attention and trust.
You are a strong communicator. You can write a technical post that a principal scientist will find rigorous and a graduate student will find accessible. You can run a panel discussion at a conference, write a newsletter, and manage an online community, and you bring a consistent point of view to all three. You are not looking for a role where the output is impressions and follower counts; you are looking for a role where the output is trust, relationships and BD.
You are comfortable building infrastructure that does not yet exist. The community playbook has not been written. The channels have not been established. The question of what Substrate's community is for and who belongs to it is still open.<h2 class="jobSectionHeader">
MUST HAVE</h2><ul><li>
Five or more years in a community, developer relations, scientific outreach, or technical partnerships role at a company serving research, life sciences, or AI scientists.</li><li>
A demonstrated ability to build a technical community from a low base: growing engagement, producing credible content, and managing relationships with researchers, scientists, or engineers.</li><li>
Strong written communication skills, with a track record of producing technical or scientific content for a specialist audience.</li><li>
Scientific or technical literacy sufficient to engage substantively with biology, data science, and AI practitioners.</li><li>
Willingness to be based in London or San Francisco, with travel to the other location and to key scientific conferences</li></ul><h2 class="jobSectionHeader">
NICE TO HAVE</h2><ul><li>
Scientific background (BSc or higher) in biology, biochemistry, computer science, or a related field.</li><li>
Experience in a developer relations or community role at a platform or infrastructure company.</li><li>
Existing relationships within the AI x biology research community AI biotechs, frontier AI labs, academic research groups, or pharma R&amp;D.</li><li>
Familiarity with the conference and events landscape for AI-driven biological discovery.</li><li>
Experience with data or API product communities.</li></ul><h1 class="jobSectionHeader">
Why this is unusual</h1>
Most community management roles sit inside companies whose community is already defined: a user base that exists, a product that is live, a channel that has followers. The job is to grow and manage something that has already started. This is not that.
Substrate's community is not yet built. The audience spans researchers, data scientists, ML engineers, and computational biologists working at the intersection of AI and wet-lab biology; it includes people in academic research groups, philanthropic foundations, frontier AI labs, pharma R&amp;D, and biotech startups, all with different professional contexts and different needs from a community of this type. Part of the job is working out who the community is for and why it exists, before building it.
The commercial adjacency is also unusual. In most companies, community and commercial are kept at arm's length: community builds trust, commercial closes deals, and the two teams share data and tooling but operate separately. At Substrate, the community function is one of the primary go-to-market channels, and the Community Manager is a genuine commercial partner.<h1 class="jobSectionHeader">
Compensation and equity</h1>
Compensation is competitive against London and San Francisco market rates for a senior community hire at a venture-backed company, calibrated to the seniority and scope of this role. Equity is meaningful, on the standard four-year vesting schedule with a one-year cliff.
We are happy to discuss the structure and philosophy in more detail with shortlisted candidates.
We sponsor visas for exceptional candidates at both the London and San Francisco locations. How we work
Hybrid, with a strong bias toward in-person time at your base location. London candidates are expected to be in person at our King's Cross lab and office most working days during the first six months; San Francisco candidates are expected to be in person at the SF node on a similar basis once the node is operational. Remote days are available and we are sensible about it, but this is a relationship-intensive role and the in-person time matters. 30 days annual leave. A learning and development budget. Quarterly offsites. We are building the rest of the benefits package as the team arrives.<h1 class="jobSectionHeader">
The team you will join</h1>
You will report to Anna Huyghues-Despointes, co-founder, who owns partnerships and go-to-market at Substrate. Anna was previously Chief Corporate Development and Strategy Officer at Owkin and an investor at Balderton Capital. You will work closely with the full founding team: Oli Hoy, who leads infrastructure build and lab delivery; Alexey Morgunov, who leads the AI and scientific intelligence work; and Mostafa ElSayed, CEO and founder of Automata, who leads the investor and government engagement side of Substrate.
Substrate is a small team growing to roughly thirty people by early 2027. This is a founding-team-adjacent hire; you will have direct access to the people making product, scientific, and strategic decisions, and your work will directly shape those decisions.<h1 class="jobSectionHeader">
How to apply</h1>
Apply via Ashby. Include a short message describing who you are, why this role makes sense for you now, and what you think the hardest part of building a technical research community from scratch will be is more useful to us than a cover letter.
Attach your CV, and, if you have produced content you are proud of, a link to it.
Our process is three stages: a first conversation with Anna, a short content task, and a founder team session in person.
If you are not certain you are a fit, send a note anyway. The community for Substrate has not been built; we are as interested in how you think about what it should be as we are in your experience doing something similar.
Substrate is an equal opportunity employer. We make hiring decisions on merit, scope-fit, and the strength of the working relationship we expect to build with each hire. Applications welcome from candidates of any background.</div>

Community Manager

Fresha

<div><h4 class="jobSectionHeader">The AI-powered OS for beauty, wellness and self-care</h4>
About Fresha 
 
Fresha is the AI-powered operating system for the global beauty, wellness and self-care industry, connecting and powering everything from salons and barbers to spas, medspas, fitness studios and health practices. 
 
Trusted by millions of consumers and businesses worldwide. Fresha is used by 140,000+ businesses and 450,000+ stylists and professionals worldwide, processing over 1 billion appointments to date. 
 
The company is headquartered in London, United Kingdom, with 15 global offices located across North America, EMEA and APAC.<div>
Fresha allows consumers to discover, book and pay for beauty and wellness appointments with local businesses via its marketplace, while beauty and wellness businesses and professionals use an all-in-one platform to manage their entire operations with an intuitive business software and financial technology solutions.</div><div>
Fresha&rsquo;s ecosystem gives merchants everything they need to run their business seamlessly by facilitating appointment bookings, point-of-sale, customer records management, marketing automation, loyalty, beauty products inventory and team management.</div><div>
The consumer marketplace unlocks revenue potential for partner businesses by leveraging the power of online bookings and automated marketing through mobile apps and advanced integrations with major tech brands including Instagram, Facebook and Google.</div><div><div><div><div><div><div><div><div><div>
We process millions of transactions and generate rich behavioural data across consumers and partners. Despite this, data science is still early at Fresha. That's the opportunity.</div></div></div></div>
About the Role
We're hiring a Head of Data Science to build DS into a core function at Fresha, not manage what already exists. Today the team is small but technically strong. We have production ML models in fraud detection, text moderation, and taxonomy classification, running on SageMaker with a dbt/Snowflake data stack. But we're operating reactively, and we know there's significantly more value DS can unlock across the marketplace.<div><div><div><div>
You'll have a clear mandate, leadership buy-in, and a technically strong team already in place. Your job is to set the direction, grow the team, and make data science visible and indispensable to how Fresha makes decisions and builds products.
This role is right for you if you've done this before - taken a small DS team at a scaling company and turned it into something the business can't operate without.
To foster a collaborative environment that thrives on face-to-face interactions and teamwork, this role will be based in our dog-friendly office 5 days per week in London: The Bower, 207-122, Old Street, London EC1V 9NR.</div></div><div>
What You'll Do</div></div></div></div><div>
Strategy &amp; Influence<ul><li>
Define the DS roadmap and align it to Fresha's business priorities across marketplace, payments, and partner growth</li><li>
Shift DS from reactive (responding to product requests) to proactive (identifying opportunities, building POCs, running demos)</li><li>
Build DS credibility with leadership - make the function visible, understood, and sought out</li><li>
Partner with Product, Engineering, and Commercial teams to embed DS into decisions</li></ul><div>
Delivery &amp; Technical Leadership<ul><li>
Ship ML products that drive measurable business impact - not just models, but outcomes</li><li>
Establish experimentation as a discipline: A/B testing infrastructure, causal inference, automated experimentation for optimisations</li><li>
Build foundational DS infrastructure: feature store, model governance, monitoring, CI/CD for ML</li><li>
Stay hands-on enough to evaluate technical decisions and architecture trade-offs</li><li>
Contribute directly to high-impact projects when needed</li></ul>
Visibility &amp; Advocacy<ul><li>
Champion DS internally through demos, stakeholder education, and proactive engagement with PMs</li><li>
Drive external visibility: engineering blog posts, conference talks, thought leadership</li><li>
Help Fresha attract top DS talent by making the function known</li></ul>
Team Building<ul><li>
Scale the team in line with what the roadmap demands - hiring across ML engineering, data science, and MLOps</li><li>
Develop the existing team, create career paths, and set technical and cultural standards</li></ul></div></div></div></div></div></div>
What the First Year Looks Like 
3 months: DS roadmap defined cross-functionally and signed off. New high-impact use cases on the table that the business hadn't previously identified. First POCs or MVPs in flight. DS is visibly present in product planning &mdash; already shifting from reactive to proactive.
6 months: Multiple ML/AI use cases shipped or in live evaluation. Experimentation is active in at least one product area. DS achievements are visible internally - demos, showcases, early external presence.
12 months: DS is a recognised, embedded function with a track record of delivery. Experimentation is a working discipline used beyond DS. MLOps maturity has stepped up. The team has grown in line with what was needed to get here.
What You Bring
Must-Haves<ul><li>
4-5 years in data science, ML engineering, or related technical fields</li><li>
3+ years directly managing and growing DS teams</li><li>
Track record of building a DS function - not just inheriting one. You've taken a team from small to meaningful and made DS matter to the business</li><li>
Shipped ML models to production at scale with real business outcomes</li><li>
Strong stakeholder management - comfortable influencing C-suite, product leaders, and commercial teams</li><li>
Technical depth to evaluate architecture decisions, review work, and call the right trade-offs</li><li>
Experience developing people - grown ICs into leads, created career ladders, built team culture</li></ul>
Nice-to-Haves<ul><li>
Experience in the marketplace, SaaS, or fintech businesses</li><li>
Familiarity with our stack: SageMaker, Snowflake, dbt, Docker</li><li>
Built or contributed to feature store, MLOps, or experimentation platform infrastructure</li><li>
Experience in establishing experimentation and A/B testing as an organisational practice</li><li>
Thought leadership - blog posts, talks, open-source contributions</li><li>
Experience making DS a &quot;core function&quot; at a company where it previously wasn't</li></ul>
Why This Role<ul><li>
Real data, real scale. Millions of transactions, 120+ countries, rich behavioural signals across a two-sided marketplace. The data is there, and there's significantly more value to unlock.</li><li>
Strong technical foundation. You're not starting from zero. There's a production ML stack, a team with deep context across the data and business, and working models in production. You're accelerating, not bootstrapping.</li><li>
Visible impact. At Fresha's stage, DS improvements flow directly to business metrics. This isn't optimising the fifth decimal place - it's building capabilities that don't exist yet.</li></ul>
Interview Process<ul><li>
Screen Stage - Video-call with a member from the Talent Team (30mins)</li><li>
1st Stage - Google Hangout - soft skills &amp; technical skills (60 mins)</li><li>
2nd Stage - In-person case study + live review with Team (60 minutes)</li><li>
Final Stage - Stakeholder interview with Deputy Chief Product Officer OR Chief Technology Officer (60min)</li></ul><div>
We aim to finalise the entire interview process and deliver feedback within 4 weeks.</div><div>
Every job application received is reviewed manually by our talent team. While we strive to assess applications within 7 days, the sheer volume of talented individuals expressing interest may occasionally extend this timeframe.</div>
Inclusive workforce<div>
At Fresha, we are creating a culture where individuals of all backgrounds feel comfortable.</div><div>
We want all Fresha people to feel included and truly empowered to contribute fully to our vision and goals. Everyone who applies will receive fair consideration for employment.</div><div>
We do not discriminate based on race, colour, religion, sex, sexual orientation, age, marital status, gender identity, national origin, disability, or any other applicable legally protected characteristics in the location in which the candidate is applying.</div><div>
If you have any accessibility requirements that would make you more comfortable during the interview process and/or once you join, please let us know so that we can support you.</div></div>

Head of Data Science

Capital One

<div>White Collar Factory (95009), United Kingdom, London, London
Data Scientist / Deep Learning Practitioner
Job Title: Data Scientist / Deep Learning Practitioner - Senior Associate/Associate level 
Location: London or Nottingham
Working Pattern: 3 days in-office (Tuesday-Thursday) and 2 days remote.
Our Mission
We&rsquo;re on a mission to be a force for good in lending. Throughout our almost 30-year history, we&rsquo;ve consistently been recognised as a great place to work; in 2026, Capital One was officially ranked 9th in the UK&rsquo;s Best Workplaces&trade; list. Hear from our team about what it&rsquo;s like working at Capital One UK.
About the Role
Our Data Science team focuses on the development of Machine Learning and Deep Learning solutions, to solve business problems and deliver actionable insights. We are a talented, collaborative and enthusiastic group, who use our expertise to derive insights from complex data, working in close collaboration with our business partners. 
This role will primarily focus on developing proprietary deep learning models to address critical business challenges in underwriting. The role will also involve supporting our business partners as they develop advanced servicing products using Large Language Models.
What you&rsquo;ll do<ul><li>
Develop new deep learning approaches to advance our current underwriting models, which form the heart of our lending business.</li><li>
Apply these to new types of (multi-modal) data in order to stay at the forefront of innovation.</li><li>
Provide consultancy to our tech and product partners, to help design, develop and launch products powered by Large Language Models (LLMs). This collaboration will help provide seamless experiences for our customers and associates.</li><li>
Use a combination of business acumen, coding and statistical skills to navigate large amounts of data and extract actionable solutions.</li><li>
Work cross-functionally on projects that support key business initiatives and drive sustainable growth.</li></ul>
The skills and experience you'll need<ul><li>
Experience developing and deploying deep learning models, particularly for sequential data (e.g. time series, language) using techniques such as LSTMs or transformers.</li><li>
Hands-on experience with modern Machine/Deep Learning frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.</li><li>
Familiarity with both pre-training and fine-tuning of large-scale models</li><li>
Experience working with structured and unstructured data, such as text, logs, or time series and tokenisation techniques.</li><li>
A strong understanding of probability, statistics, machine learning and familiarity with large data set manipulation.</li><li>
Experience in producing reliable and maintainable code in Python, with an ability to adapt to new languages and technologies.</li><li>
Ability to communicate findings to a diverse business focused audience, influencing others in both verbal and written form.</li><li>
A drive for continued learning through an internal and external focus, in order to develop enterprise and industry leading solutions.</li></ul>
Where and how you'll work
This is a permanent position based in our Nottingham OR London office.
We embrace a hybrid approach to work. You'll spend three days a week in the office (Tuesday-Thursday), with Monday and Friday being dedicated work-from-home days.
Our offices are designed to inspire and support you. At our Nottingham head office, you'll find an on-site gym, restaurant and dedicated Learning Loft. Our London office boasts a rooftop running track and coffee bar.
What&rsquo;s in it for you
We invest in the growth of our people alongside our business. You will have extensive opportunities to learn and develop your career, including access to up to &pound;5,000 in funding for external qualifications.
In addition to career development, our comprehensive benefits package is designed to grow with you, ensuring your wellbeing is prioritised at every stage of your career:<ul><li>
Wealth &amp; Future: Competitive pension and performance-based bonus schemes</li><li>
Holidays: Start with 25 days of annual leave, increasing with tenure. Need more? You have the option to buy 5 additional days.</li><li>
Health: Access premium care through our private medical insurance.</li><li>
Family Support: We champion your milestones with enhanced parental leave.</li></ul>
A full list of our benefits is available here.
What you should know about how we recruit
We pride ourselves on hiring the best people, not the same people. Building diverse and inclusive teams is the right thing to do and the smart thing to do. We want to work with top talent: whoever you are, whatever you look like, wherever you come from. We know it&rsquo;s about what you do, not just what you say. That&rsquo;s why we make our recruitment process fair and accessible.
We value diversity, inclusion and belonging at our core. We empower our associates to do great work by creating an inclusive culture&mdash;one that values diverse perspectives, fosters collaboration and encourages innovative ideas&mdash;and a place where associates of all backgrounds can thrive by bringing their most authentic selves to work. We call this our Culture of Belonging, and it rests at the heart of our business.
Our associate-led Business Resource Groups were created to help support our diverse population and include over 10 groups across our offices. Because each Business Resource Group is as unique as the population it serves, they offer a range of activities, networking opportunities, special events and learning programmes to associates.
Capital One is committed to diversity in the workplace.
If you require a reasonable adjustment, please contact ukrecruitment@capitalone.com All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment.<div><div><div><div>
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div></div></div></div> 
Who We Are 
 
At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding. 
 
Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.</div>

Data Scientist / Deep Learning Practitioner

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