Location: London
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
- 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
- Strong hands‑on experience with Databricks
- Proven experience building production-grade data and ML pipelines
- Solid understanding of MLOps principles
- Experience working with machine learning models
- Experience with GCP
- Background in both Data Engineering and Machine Learning Engineering environments
- Exposure to scalable, high-performance data platforms
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 with high likelihood of extension, apply now to be considered.
#J-18808-Ljbffr”, “datePosted”: “2026-05-21”, “hiringOrganization”: { “@type”: “Organization”, “name”: “DW Search”, “sameAs”: “https://uk.whatjobs.com/pub_api__cpl__438846264__4861?utm_campaign=publisher&utm_medium=api&utm_source=4861&geoID=33” }, “jobLocation”: { “@type”: “Place”, “address”: { “@type”: “PostalAddress”, “addressLocality”: “London” } } }Location: London
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
- 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
- Strong hands‑on experience with Databricks
- Proven experience building production-grade data and ML pipelines
- Solid understanding of MLOps principles
- Experience working with machine learning models
- Experience with GCP
- Background in both Data Engineering and Machine Learning Engineering environments
- Exposure to scalable, high-performance data platforms
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 with high likelihood of extension, apply now to be considered.
#J-18808-Ljbffr…