Senior ML /AI

Senior ML /AIWork location- Paya LebarThe ML/AI Engineer sits within the DSAD Platform and Architecture Team and is responsible for productionising,operating and improving machine-learning and AI workloads on the SWDA data platform using AWS and Databricks.Experience: Typically 4–7 years of relevant software, data or ML engineering experience, including hands-on deliveryand operation of ML/AI systems beyond prototype stage. Candidates with fewer years but strong evidence of end-toendproduction ownership may also be considered.B. Technical & Professional CompetenciesEssential (Must-Have)• Strong Python and software-engineering capability, including APIs, packaging, automated testing, Git, codereview, debugging and modular design.• Hands-on experience with Databricks and MLflow for experiment tracking, model registry, workflow orchestrationor model serving.• Strong hands-on experience with Spark/PySpark and SQL, including distributed data processing, queryoptimisation, partitioning, joins, incremental processing and troubleshooting data pipelines.• Experience designing and implementing lakehouse or data-lake pipelines using Databricks, Delta Lake and AWSS3, including Bronze, Silver and Gold data-layer patterns.• Experience with data modelling, schema design, data contracts, metadata, lineage, data-quality validation andreconciliation for production analytics and ML datasets.• Experience orchestrating batch or streaming workflows using Databricks Workflows, AWS Glue, Step Functions,EventBridge, Apache Airflow or an equivalent enterprise orchestration tool.• Hands-on AWS data and cloud engineering experience with a relevant mix of S3, Glue, Lake Formation, IAM, KMS,ECR, ECS/EKS, Lambda, Step Functions, EventBridge, CloudWatch, API Gateway, Secrets Manager, Redshift,MSK/Kinesis or equivalent approved services.• Experience with Docker, infrastructure as code such as Terraform, and CI/CD platforms such as GitLab CI,GitHub Actions, Jenkins or Harness.