Machine Learning Engineer, National Job-Skills Data Office (INTD)
Core
Design, build, and deploy scalable machine learning systems and data pipelines to power real-world applications for workforce planning and jobs-skills intelligence.
Role type
Machine Learning Engineer (MLOps & Data Infrastructure)
Builds
Scalable AI/ML infrastructure, robust data pipelines, and production-ready AI models integrated with data warehouses and APIs.
Domain
Government workforce planning, skills intelligence, and data management.
Deliverable
production ML models | infrastructure
Required skills
Python, SQL, TensorFlow, PyTorch, scikit-learn, CI/CD, DevOps, containerization, data governance, model monitoring, drift detection, automated retraining, data warehousing, cloud platforms.
Preferred skills
Experience with large-scale datasets, third-party AI tools integration, cross-functional collaboration.
Technologies
TensorFlow, PyTorch, scikit-learn, data warehouses, APIs, containerization, version control, orchestration.
Responsibilities
Design and implement scalable AI/ML infrastructure; develop and deploy robust AI solutions; optimize and maintain ML model performance; build and maintain end-to-end data architecture; implement MLOps and CI/CD processes; ensure system reliability and governance compliance; drive cross-functional collaboration.
Seniority
Mid-to-Senior, hands-on IC
