Underlying cloud infrastructure runs on Google Cloud Platform (GCP), so working familiarity with GCP is helpful for collaborating with the platform team
· Emerging-Risk Agent Development: Develop AI agents that analyse approved information sourcesto identify, generate and prioritise evidence-linked emerging fraud and abuse risks for officer review.
Operate and extend the Studio engine: image generation (gpt-image-2), video generation (Seedance 2.0 via BytePlus), reference-anchored character consistency, take/cut/release pipelines
Experience designing and implementing lakehouse or data-lake pipelines using Databricks, Delta Lake and AWSS3, including bronze, silver and gold data-layer patterns.
Work within established AI-native engineering workflows, collaborating with AI agents across implementation, testing, debugging, and documentation while validating every output.
Regulatory support: Contribute technical documentation, validation evidence, and risk assessments aligned with SaMD requirements (FDA/HSA, ISO 13485/62304), working alongside our clinical and regulatory leads.
Implement policies and controls: Translate applicable IM8, Whole-of-Government RAI and agency requirements into practical checklists, assessment templates and workflows. Review and update these materials as requirements and use cases evolve, under DSAD’s direction.
Agentic AI Development: Design and prototype autonomous “agentic” systems capable of analyzing production logs, diagnosing anomalies, and recommending corrective actions to engineers.
We are looking for a Computer Vision AI Engineer Intern who wants to learn how vision models go from training to working on real cameras in the real world. You will support our senior engineers on model development, and you will also get hands-on experience helping set up and fine-tune systems at customer sites, something most interns never get to see.