Senior Machine Learning Engineer

DW Search; Greater London; Hybrid; GBP 92,250 - 129,150; Full time

Job summary

DW Search is looking for a Senior Machine Learning/ MLOps / Data Engineer for a hybrid role in London. This contract opportunity involves working on building and productionising ML pipelines within a dynamic environment for a major asset management firm.

The successful candidate will have strong Python skills and a solid background in MLOps. Responsibilities include deploying machine learning models and collaborating with teams to enhance model performance. This is an initial 6-month contract, outside IR35, potentially extendable.

Qualifications

• Proven experience building production-grade data and ML pipelines.
• Solid understanding of MLOps principles.
• Experience working with machine learning models.

Responsibilities

• Build and productionise feature engineering pipelines for ML models.
• Develop and manage training and inference workflows at scale.
• Deploy and monitor machine learning models in production environments.
• Collaborate with teams to optimise model performance.

Skills

Strong Python fluency

Building production-grade data and ML pipelines

Understanding of MLOps principles

Working with machine learning models

Project experience with Databricks

Cloud experience (Azure/GCP/AWS)

Job description

Senior Machine Learning/ MLOps / Data Engineer

London - Hybrid Working

DW Search are partnering on a high-impact contract opportunity within a fast-paced, data-driven environment supporting portfolio company initiatives for a major asset management firm.

This role sits at the intersection of Data Engineering and Machine Learning Engineering, with a strong focus on building and productionising end-to-end ML pipelines. You will be working on real-world applications of neural networks, enabling scalable feature engineering, model training, and inference in production.

Key Responsibilities

• Build and productionise feature engineering pipelines for ML models (neural networks)
• Develop and manage training and inference workflows at scale
• Deploy and monitor machine learning models in production environments
• Collaborate with data scientists and engineering teams to optimise model performance and reliability
• Contribute to best practices across MLOps and pipeline orchestration

Required Experience

• Strong Python fluency
• Proven experience building production-grade data and ML pipelines
• Solid understanding of MLOps principles
• Experience working with machine learning models
• Some project experience with Databricks
• Cloud experience - open to Azure/ GCP/ AWS

This is a strong fit for engineers who operate across the full ML lifecycle and enjoy taking models from development into robust, production systems.

This is an initial 6 month contract, outside IR35 with high likelihood of extension.

A rate guidance is provided but the focus is on the right person so open to contractors outside of this range.