Senior Data/ML Platform Engineer at DW Search, London Area, £Negotiable Rate

Senior Data / ML Platform Engineer

Contract | Outside IR35 | London - Hybrid

£600-£700 (negotiable)

DW Search is partnering with a rapidly growing organisation undertaking a significant data and machine learning transformation.

We're looking for a senior engineer who can help bridge the gap between data engineering, platform engineering, and machine learning operations. This role focuses on building the systems, workflows, and infrastructure that enable machine learning models to move from experimentation into reliable production use.

This is not a research or modelling role. Instead, you'll work closely with Data Scientists and engineering teams to productionise machine learning workflows, improve platform capabilities, and build scalable foundations for future AI and ML initiatives.

What you'll be doing

• Build and optimise production-grade data and machine learning pipelines
• Develop feature engineering workflows that support model training and inference
• Design and improve orchestration, automation, and scheduling frameworks
• Implement experiment tracking, model lifecycle management, and monitoring capabilities
• Build and maintain feature stores and supporting platform components
• Improve the scalability, reliability, and performance of training and inference workflows
• Work closely with Data Scientists to help operationalise machine learning solutions
• Contribute to platform architecture, engineering standards, and tooling decisions

What we're looking for

• Strong software, platform, or data engineering background
• Experience supporting machine learning workloads in production
• Strong Python and distributed data processing experience (PySpark or similar)
• Experience with workflow orchestration tools such as Airflow, Dagster, Prefect, or similar
• Experience with machine learning platforms and tooling such as MLflow, SageMaker, Vertex AI, Azure ML, Databricks ML, or equivalent
• Understanding of feature engineering, feature stores, experiment tracking, and model deployment workflows
• Experience working alongside Data Scientists and helping productionise machine learning solutions
• Strong understanding of monitoring, observability, scalability, and operational excellence

Nice to have

• Experience supporting PyTorch-based workloads
• Experience optimising model training or inference pipelines
• Exposure to distributed compute environments
• Experience building internal ML platforms or MLOps capabilities from the ground up

The opportunity

This is an opportunity to join a business investing heavily in modern data and machine learning capabilities. You'll play a key role in shaping the underlying platform and engineering practices that enable ML solutions to operate reliably at scale and deliver measurable business impact.