Senior Machine Learning Engineer
Posted Today by DW Search
£90 Per hour
Outside
Hybrid
London Area, United Kingdom
Summary: The Senior Machine Learning Engineer role involves building and productionising end-to-end machine learning pipelines within a major asset management firm. The position requires collaboration with data scientists and engineering teams to optimize model performance and reliability in a fast-paced, data-driven environment. This contract role is hybrid and focuses on deploying machine learning models in production settings. The contract is outside IR35 with a high likelihood of extension.
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
Key Skills:
- 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
Salary (Rate): £90.00/hr
City: London
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: outside IR35
Seniority Level: Mid-Level
Industry: IT
Senior Machine Learning/ MLOps / Data Engineer
London - Hybrid Working
Contract - Outside IR35
£600-£700 per day
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.