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Senior AI Engineer, Platform Engineering - Resmed
AI Engineer
Lead the design and deployment of AI-driven services on a scalable, secure platform, leveraging Python, ML frameworks, and cloud-native tools to deliver high‑performance solutions for global health applications.
About the role
Key Responsibilities
- Architect and implement end‑to‑end AI pipelines, from data ingestion to model serving, on AWS and Kubernetes clusters.
- Collaborate with cross‑functional teams to define platform standards, ensuring scalability, security, and compliance across global deployments.
- Develop reusable microservices and containerized workloads using Docker, Helm, and CI/CD pipelines.
- Optimize model performance and resource utilization, applying techniques such as model quantization and autoscaling.
- Mentor junior engineers and conduct code reviews, fostering best practices in software engineering and ML operations.
Requirements
- 5+ years of experience in AI/ML engineering with a strong background in Python and popular ML libraries (TensorFlow, PyTorch).
- Proven expertise in deploying AI workloads on AWS (SageMaker, ECS/EKS) and managing Kubernetes clusters.
- Hands‑on experience with Docker, Helm, and CI/CD tools (GitHub Actions, Jenkins, ArgoCD).
- Solid understanding of data engineering concepts, including data pipelines, ETL, and data lake architectures.
- Excellent problem‑solving skills, strong communication, and a collaborative mindset.
Skills
pythonmachine learningawskubernetesdockercicd