KDR Talent Solutions
Head of Machine Learning

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Head of AI/ML Platform & Engineering
📍 UK / Remote | 🌍 Global Impact | 🚀 Cutting-edge AI & Data Platform
We are partnering with a global leader in insights, analytics, and technology to appoint a Head of AI/ML Platform & Engineering. This is a rare opportunity to shape and scale a next-generation platform at the intersection of generative AI, machine learning, and privacy-first data systems.
The Opportunity
You’ll be joining a highly innovative, cross-disciplinary team building a world-class synthetic data platform used at global scale. This platform is central to driving future-facing capabilities such as:
- AI-powered data augmentation tools
- “Digital twin” models simulating real-world behaviours
- Secure, compliant frameworks for synthetic data generation
This is a unique chance to lead engineering for a product that blends scientific rigour with real-world impact, collaborating with leading academic partners and internal experts across data science, engineering, and research.
The Role
As Head of Platform & Engineering, you’ll define the technical direction and lead the delivery of a secure, scalable, enterprise-grade platform used globally.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
You will:
- Set the engineering vision and architecture, ensuring the platform scales to support complex, compute-heavy AI workloads
- Build and lead a high-performing team across software, data, and MLOps engineering
- Bridge research and production, translating advanced ML into robust, real-world systems
- Establish best-in-class engineering standards, from SDLC maturity to operational excellence
- Embed privacy, security, and governance into every layer of the platform
- Enable self-serve capabilities, empowering teams to safely generate and experiment with synthetic data
- Optimise cloud infrastructure and costs, balancing performance with efficiency
Technology Environment
You’ll operate within a modern, cloud-native ecosystem including:
Cloud & Infrastructure:
- GCP, Kubernetes (GKE), Docker, Terraform/Pulumi
MLOps & AI Platforms:
- Vertex AI, Kubeflow, model registries, ML CI/CD
Backend:
- Python, FastAPI, async frameworks (Celery/RabbitMQ)
Data:
- BigQuery, distributed processing, vector databases
AI/ML:
- PyTorch, LLMs, generative models
What We’re Looking For
Technical Leadership
- Proven experience scaling and leading cross-functional engineering teams
- Strong background in distributed systems and cloud-native architecture
- Expertise in building highly available, scalable platforms


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MLOps / GenAI Experience
- Experience delivering ML platforms, pipelines, and production models
- Understanding of LLM deployment, GPU workloads, and vector databases
- Familiarity with the challenges of productionising AI
Commercial & Stakeholder Skills
- Ability to align engineering with business and product strategy
- Strong collaboration across research, product, and executive teams
- Knowledge of enterprise security, governance, and compliance frameworks
Why Apply?
- Shape a greenfield, high-impact platform at scale
- Work at the forefront of synthetic data and generative AI innovation
- Collaborate with top-tier talent across engineering and research
- Influence how global organisations generate and use data in the future
If you're a hands on, visionary engineering leader with a passion for AI platforms and building high-performing teams, we’d love to hear from you.
👉 Apply now or get in touch for a confidential discussion.
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