Senior ML/AI Engineer - AWS, Databricks & MLOps (Public Sector)
Core
Build engineering foundations for reliable production ML/AI systems, turning experiments into maintainable services and pipelines on AWS and Databricks.
Role type
Senior hands-on IC ML/AI Engineer (MLOps)
Builds
Reusable MLOps components, productionized batch jobs/APIs, data pipelines, and operational AI services for public sector workloads.
Domain
Public sector technology, Cloud infrastructure (AWS), Data Engineering, Machine Learning Operations
Deliverable
production ML models
Required skills
Python software engineering, PySpark, SQL, Databricks, MLflow, AWS cloud services, Docker, Terraform, CI/CD, data modeling, observability
Preferred skills
Unity Catalog, Delta Live Tables, Generative AI productionization, Kubernetes, OpenTelemetry, A/B testing
Technologies
AWS (S3, Glue, IAM, KMS, Lambda, ECR, ECS/EKS, CloudWatch, Redshift), Databricks, Delta Lake, MLflow, Terraform, GitLab CI, GitHub Actions, Jenkins, Harness, Kubernetes, Prometheus, Grafana
Responsibilities
Design reusable MLOps components for tracking, registry, orchestration, deployment, and monitoring; Productionise notebooks into modular batch jobs and APIs; Build reliable data and feature engineering pipelines; Optimize Spark/SQL workloads for performance and cost; Automate testing and promotion via CI/CD; Implement versioning, lineage, and retirement mechanisms; Build monitoring dashboards and support incident diagnosis; Develop regression-testing practices; Apply cloud security and responsible-AI controls.
Seniority
Senior, hands-on IC
