GCP + Machine Learning Optimisation Consultant

Job Title: GCP & ML Optimisation consultant (Fraud) Role summary Outcome-based optimisation assessment , implementation-ready Hrecommendations 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; optimise 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 (e.g., reduced compute, faster inference, improved automation). ML/data pipelines: Optimise 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).