Senior GCP ML Optimization
We are a Global Recruitment specialist that provides support to the clients across EMEA, APAC, US and Canada. We have an excellent job opportunity for you.
Role Title: Senior GCP ML Optimization
Location: Sheffield
Duration: 31/12/2026
Work setup: 3 days onsite/week
Rate: £492 per day all inc. (PAYE through Umbrella)
Role Description: Data Scientist | L4
- Outcome-based optimization assessment, implementation-ready recommendations role, with explicit expectations for hands-on analysis on optimizing fraud Models, ML platform on Google Cloud by reducing run-cost & Improving performance and reliability across GCP infrastructure, ML pipelines .You'll apply strong engineering discipline and collaborate with IT Infra, data scientists and fraud stakeholders to deliver measurable compute and inference savings.
- Produce workable, implementable recommendations with effort/cost savings
- Provide configuration-level and code-level guidance
Key responsibilities:
- GCP engineering: Hands-on design and diagnostics; optimize compute/storage/network trade-offs to reduce run-cost; implement monitoring and observability for cost, performance, and reliability.
- Fraud ML modelling support: Support building, validating, and deploying fraud/ML models end-to-end, with demonstrated cost savings (eg, reduced compute, faster inference, improved automation).
- ML/data pipelines: Optimize pipelines from ingest - transform - feature creation/serving - training/inference, focusing on cost efficiency, performance, and resilience.
- Big data & distributed processing:* Develop and tune large-scale batch/stream workloads (Spark or similar); improve job efficiency, stability, and operational readiness in production.
- Software engineering:* Strong Python + SQL; apply CI/CD, automated testing, modular design, and disciplined code reviews.
Desired (bonus):
- Feedzai: Exposure to or implementation experience with Feedzai (integration, performance tuning, operationalisation).
If you are interested in this position and would like to learn more, please send through your CV and we will get in touch with you as soon as possible. Please note, candidates are often Shortlisted within 48 hours.