Responsibilities Accountable for the end-to-end build and engineering of the production ML / AI application taking a prototype model from the data scientists and developing a production-ready application using appropriate tools and technologies to deploy using AWS cloud. Accountable for the successful development resilience and reliability of the analytical model scoring application pipelines. Follow the established patterns to make the ML / AI models ready for deploy to pre-prod and prod environments with MLOps engineers. Study and transform data science prototypes understanding the requirements and designing the application. Understand the container environments for where these applications can reside. Build re-training pipelines with the MLOps engineers to enable automation of regular and ad hoc re-training. Extend existing ML libraries and frameworks defining best practice and supporting the development of our technology roadmap and cloud analytics strategy. Continuous improvement and transformation initiatives for ML/ AI and MLOps in project. Support for the tools and platform used to develop and deploy analytical models within AWS. Building on or MLOps foundation to deliver an enterprise wide machine learning capability based on AWS Sagemaker and other AWS services. Define MLOps tools strategy for Release Orchestration CI/CD Pipelines etc. Collaborate with teams to synchronise CI/CD activities with MLOps Data Scientists and Data Engineers. Expertise in Python yaml json AWS Sagemaker and other services. Good to have - Airflow MLFlow and AWS Bedrock experience Qualifications Bachelors degree in computer science engineering. 8+ years experience in Python development role AWS and DS. Experience working in MLOps and real time streaming pipeline Ability to communicate effectively. Strong process documentation skills. Named Job Posting? (if Yes - needs to be approved by SCSC)Additional Details

Global Grade C

Level To Be Defined

Named Job Posting? (if Yes - needs to be approved by SCSC) No

Remote work possibility Yes

Global Role Family 60242 (P) Data Management

Local Role Name 60327 Data Engineer

Local Skills 58895 Machine Learning

Languages RequiredEnglish

Role Rarity To Be Defined

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IN | ML Engineer