Senior ML /AI

Senior ML /AI
Work location- Paya Lebar

The 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 delivery

and operation of ML/AI systems beyond prototype stage. Candidates with fewer years but strong evidence of end-toend

production ownership may also be considered.

B. Technical & Professional Competencies

Essential (Must-Have)

. Strong Python and software-engineering capability, including APIs, packaging, automated testing, Git, code

review, debugging and modular design.

. Hands-on experience with Databricks and MLflow for experiment tracking, model registry, workflow orchestration

or model serving.

. Strong hands-on experience with Spark/PySpark and SQL, including distributed data processing, query

optimisation, partitioning, joins, incremental processing and troubleshooting data pipelines.

. Experience designing and implementing lakehouse or data-lake pipelines using Databricks, Delta Lake and AWS

S3, including Bronze, Silver and Gold data-layer patterns.

. Experience with data modelling, schema design, data contracts, metadata, lineage, data-quality validation and

reconciliation 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.