MLOps Engineer (Databricks & AWS) | Gov| Contract

Your tasks

• Design and implement MLOps/AIOps platform components for experiment tracking, model deployment, monitoring and retraining using Databricks, MLflow and AWS.
• Productionise ML/AI prototypes into scalable, tested and maintainable pipelines, APIs and model-serving services.
• Build and maintain feature engineering pipelines using Databricks, PySpark, SQL and AWS.
• Develop automated CI/CD/CT workflows for code, data, models and infrastructure deployment.
• Implement model versioning, experiment tracking, data lineage, reproducibility and governance controls.
• Monitor system health, model performance, data quality, drift, resource utilisation and cloud costs.
• Optimise Spark workloads, data pipelines and model-serving infrastructure for performance and reliability.
• Establish model evaluation, regression testing, A/B testing and deployment rollback processes.
• Implement cloud security, access controls, audit logging and Responsible AI safeguards.
• Support recommendation and search systems through model maintenance, retraining, experimentation and performance optimisation.
• Maintain technical documentation, operational runbooks and deployment records, and support knowledge transfer across teams.

Requirements

Requirements & Qualifications

• Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems or a related field.
• Typically 4–7 years of relevant software, data or ML engineering experience, with hands-on experience deploying and operating production ML/AI systems.
• Strong Python programming and software engineering skills, including API development, automated testing, Git and modular design.
• Hands-on experience with Databricks and MLflow for experiment tracking, model registry, workflow orchestration or model serving.
• Strong proficiency in PySpark, Apache Spark and SQL, including distributed data processing and pipeline optimisation.
• Experience with Databricks, Delta Lake and AWS S3 for production data pipelines and lakehouse architectures.
• Experience with feature engineering, data validation, model evaluation, deployment, monitoring and retraining.
• Familiarity with AWS services such as Glue, IAM, Lambda, Step Functions, CloudWatch and related cloud services.
• Experience with Docker, CI/CD tools and infrastructure-as-code solutions such as Terraform.
• Knowledge of model monitoring, drift detection, reproducibility, rollback procedures and cloud security.
• Strong problem-solving, communication and cross-functional collaboration skills.

Preferred Skills

• Experience with Unity Catalog, Delta Live Tables, Lakeflow or feature stores.
• Familiarity with Kubernetes, Airflow, Kafka, AWS MSK/Kinesis or event-driven architectures.
• Experience productionising generative AI or agentic AI applications.
• Knowledge of OpenTelemetry, Prometheus, Grafana, A/B testing or champion-challenger deployment.
• Experience supporting recommendation engines, search systems or high-volume AI services.
• Familiarity with Singapore public-sector security, governance and Responsible AI requirements.

How to apply

Interested candidates are invited to apply via the “Apply Now” button.

Nexbridge Recruitment Pte Ltd|26C3616 EA Personnel: Guan Jiayi|R22109847

Other

We regret that only shortlisted candidates will be notified.