Data and AI Engineer (GCP & Vertex AI) | London | Remote | Competitive salary DOE
If you want to work at the intersection of Data and ML as a modern Data Engineer on GCP this is the role for you.
This is an opportunity to join a market leading client that is building next-generation products and platforms leveraging large-scale data processing, machine learning, and generative AI technologies. They are making significant long-term investment in Google Cloud, with GCP and Vertex AI sitting at the centre of their future technology strategy.
Why this role stands out:
- Work at the intersection of Data Engineering and Machine Learning
- Build on a modern, GCP-first technology stack with Vertex AI as a core platform capability
- Develop platforms and services that power next-generation AI and generative AI applications
- Significant ownership and influence over platform design and technical direction
- Join a multidisciplinary team of engineers, researchers, and data scientists working on genuinely cutting‑edge challenges
The role:
As a Data and AI Engineer, you'll operate where Data Engineering and Machine Learning Engineering converge.
Part of your role will involve designing and building the data foundations that make machine learning possible, creating scalable data pipelines, optimising data movement, and ensuring high-quality datasets are available for experimentation and production use. Equally, you'll help build the infrastructure and services that enable AI applications to run reliably at scale, supporting model development, training, inference, and deployment workflows on GCP.
It's a broad engineering role that would suit someone who enjoys working across traditional boundaries and wants to be involved in the full lifecycle of modern data and AI systems.
You’ll be responsible for:
- Building scalable data pipelines that support analytics and machine learning workloads
- Designing and developing cloud-native platforms on Google Cloud Platform
- Developing services and APIs that connect applications with AI and data processing workflows
- Enabling machine learning and generative AI use cases through robust platform engineering
- Supporting model training, experimentation, and deployment workflows on Vertex AI
- Improving platform reliability, observability, and data quality standards
- Working closely with engineers, data scientists, and researchers to deliver production-grade AI solutions
- Optimising data storage and processing for high-volume, compute-intensive workloads
- GCP
- BigQuery
- Python
- Kubeflow and MLOps tooling
- FastAPI
- Vector databases and modern RAG tooling
What we’re looking for:
- Experience building cloud-native data platforms on GCP
- Hands‑on experience with Vertex AI and familiarity with modern machine learning workflows
- Excellent Python and SQL engineering skills
- Experience developing modern data pipelines and orchestration frameworks
- Understanding of MLOps principles and the infrastructure required to support machine learning systems in production
- Exposure to unstructured data workloads, vector search, or LLM applications would be highly beneficial
This is an opportunity to join an organisation making a serious investment in their Data and ML Engineering capability, working on genuinely interesting technical challenges and helping build the platforms that will underpin the next generation of intelligent products and services.
