First-class IT Recruitment Solutions

• Leading a team of data engineers while staying hands-on with design and coding
• Owning the technical direction and architecture of data pipelines and platforms
• Building and maintaining production-grade data workflows using Python, SQL, Snowflake, and DBT
• Designing cloud-based data solutions on AWS using serverless and event-driven patterns
• Setting engineering standards around code quality, testing, CI/CD, and documentation
• Ensuring data platforms are reliable, observable, and cost-efficient in production
• Working closely with business and technical stakeholders to turn requirements into working solutions
• Mentoring engineers and raising the overall engineering bar

• Strong experience in Python and SQL, with a software engineering mindset
• Proven hands-on experience with Snowflake and modern data modelling practices
• Solid background in data engineering (ETL/ELT, orchestration, data quality)
• Practical experience building data systems on AWS
• Experience defining architecture and making technical trade-offs
• Confidence leading technical initiatives and supporting other engineers
• Strong communication skills and comfort working with non-technical stakeholders

• Experience with workflow orchestration tools (e.g. Airflow)
• Exposure to APIs, streaming data, or real-time processing
• Familiarity with regulated or compliance-heavy environments
• Experience improving platform reliability, performance, or cloud costs

• High-impact position with real ownership and influence
• A balance of leadership and hands-on technical work
• Opportunity to shape long-term data architecture and standards
• Collaborative environment with complex, real-world data challenges

Machine Learning Scientist - Recommendations

Fully Remote contract (UK / Europe), Outside IR35, 6 months initially

We're partnering with a consumer-facing technology company operating at significant scale, supporting millions of users across multiple products. They are looking for a Machine Learning Scientist to join a high-impact People Recommendations team, working at the intersection of applied research and real-world product delivery. This role suits someone who enjoys taking ideas from research to production, owning the full model lifecycle and pushing the boundaries of modern recommendation systems in a two-sided marketplace.

As a Machine Learning Scientist, you'll design and evolve recommendation algorithms that directly shape how users connect and interact. You'll work closely with Data Scientists, Machine Learning Engineers, and Platform Engineers, acting as the bridge between research intuition and production reality. You'll have real ownership, autonomy, and influence, from early-stage experimentation through to models running in production at scale.

What You'll Be Doing

Research & Prototype (0 → 1)

• Explore novel approaches to bilateral matching, user representation learning, and preference modelling
• Prototype new architectures tailored to two-sided marketplaces
• Stay close to state-of-the-art research and translate relevant advances from paper to prototype

Build & Ship (1 → N)

• Evolve and improve production recommendation models, including Transformer and Graph Neural Network (GNN) based approaches
• Design robust evaluation frameworks that reflect real marketplace success
• Run large-scale experiments to test hypotheses and iterate quickly

Collaborate & Influence

• Partner with Product to define what's technically feasible and what trade-offs matter
• Work closely with ML Engineers to ensure models are reliable, scalable, and production-ready
• Mentor others, contribute to technical direction, and influence best practice across the team

What We're Looking For

Essential:

• MSc or PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field
• Strong experience designing, training, and shipping modern deep learning models
• Production-level Python skills and experience with frameworks such as PyTorch
• End-to-end ML lifecycle experience: feature engineering, training, evaluation, deployment, and monitoring
• Comfortable operating in ambiguous problem spaces and structuring solutions from scratch
• Strong communication skills and ability to work with both technical and non-technical stakeholders
• A thoughtful approach to AI fairness, accountability, and transparency

Nice to Have:

• Experience with recommendation systems, ranking, or search, especially in two-sided marketplaces
• Exposure to modern LLM deployment frameworks (e.g. HuggingFace TGI, vLLM, TensorRT-LLM)
• Production experience on GCP (Vertex AI, BigQuery, GKE)
• Understanding of GPU-powered workloads, container runtimes, and NVIDIA tooling

Senior Data Engineer - Data Analytics & AI

We're working with a global organisation undergoing a major data and AI transformation, and they're looking to hire an experienced Senior Data Engineer to join a high-impact Data Analytics & AI function.

This role sits within a large-scale operations and technology environment where data directly supports critical, real-world outcomes. You'll be building robust, scalable data platforms that power advanced analytics, AI and decision-making across complex, regulated domains.

The Role

As a Senior Data Engineer, you'll design, build and optimise modern data pipelines and platforms, ensuring data is reliable, accessible and ready for advanced analytics and AI use cases.

You'll work closely with data scientists, analysts, architects and stakeholders to deliver high-quality data products end-to-end, using modern cloud and data engineering best practices.

Key Responsibilities

• Design, build and maintain scalable, high-performance data pipelines

• Develop and optimise ETL / ELT processes for complex data sources

• Improve pipeline performance, reliability and efficiency

• Troubleshoot and resolve data pipeline and application issues

• Collaborate with cross-functional teams to deliver trusted, analytics-ready datasets

• Work extensively with cloud-based data platforms (AWS)

• Ensure data quality, integrity and validation across systems

• Contribute to CI/CD pipelines, version control and automated deployments

• Create and maintain technical documentation and data models

• Ensure data solutions follow FAIR data principles

• Stay current with emerging data engineering and AI technologies

Essential Skills & Experience

• 7+ years' experience in Data Engineering / Software Engineering

• Strong experience with ETL / ELT tools (e.g. SnapLogic, Fivetran or similar)

• Deep hands-on experience with Snowflake and DBT

• Advanced SQL and data modelling skills

• Strong knowledge of data pipeline architecture, dimensional modelling and integration patterns

• Experience with Data Mesh / Data Product concepts

• Cloud expertise, particularly AWS (S3, EC2, RDS, Lambda, Airflow/MWAA, ECS/EKS)

• Strong Python and/or Java development skills

• Experience with CI/CD, GitHub and DevOps practices

• Exposure to automated testing (unit, integration, regression, data testing)

• Excellent communication skills and experience working with senior stakeholders

• Comfortable working in Agile environments