Senior ML/AI Platform Engineer

SEDHA CONSULTING PTE. LTD.; Singapore; Sur place; SGD 120 000 - 180 000; Plein temps

Résumé du poste

SEDHA CONSULTING PTE. LTD.

is seeking a Senior ML/AI Engineer (Senior Consultant) to drive end-to-end ML/AI platform initiatives in Singapore. You will build reliable data and feature pipelines, curate production-ready datasets, and establish reusable MLOps/AIOps capabilities that support secure, observable, and cost-effective AI services across data ingestion, experimentation, deployment, monitoring, retraining, and retirement.

Qualifications

• Strong Python and software-engineering capability, 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 for distributed data processing and pipeline troubleshooting.
• Experience designing lakehouse/data-lake pipelines with Databricks, Delta Lake and AWS S3.

Responsabilités

• Design and implement reusable platform components and golden paths for experiment tracking and deployment.
• Convert notebooks and prototypes into modular, tested services and endpoints with operational ownership.
• Design and maintain feature engineering pipelines on Databricks and AWS for ML datasets.

Connaissances

Python

APIs

Packaging

Automated testing

Git

Code review

Debugging

Modular design

Formation

Degree in Computer Science, AI, Data Science, Software Engineering, Information Systems or related field

Outils

Databricks

MLflow

Spark/PySpark

SQL

Delta Lake

AWS S3

Terraform

GitLabCI

GitHub Actions

Jenkins

Harness

Description du poste

SEDHA CONSULTING PTE. LTD.

is seeking a Senior ML/AI Engineer (Senior Consultant) to drive end-to-end ML/AI platform initiatives in Singapore. You will build reliable data and feature pipelines, curate production-ready datasets, and establish reusable MLOps/AIOps capabilities that support secure, observable, and cost-effective AI services across data ingestion, experimentation, deployment, monitoring, retraining, and retirement.