3 days ago
Sydney, Australia or Melbourne, AustraliaSenior
Responsibilities
- Build and deploy production-grade machine learning software, tools, and infrastructure.
- Create reusable and scalable solutions that accelerate delivery of ML systems.
- Collaborate with engineers, data scientists, and commercial leads to solve client challenges.
- Lead technical scoping and architectural decisions for project feasibility and impact.
- Define and implement standards for deploying machine learning at scale.
- Act as a technical advisor to customers and partners and explain complex ML concepts to stakeholders.
Requirements
- Understand the full machine learning lifecycle and have experience operationalizing models built with Scikit-learn, TensorFlow, or PyTorch.
- Demonstrate strong Python skills and solid software engineering best practices.
- Have hands-on experience with cloud platforms and infrastructure such as AWS, Azure, or GCP, including architecture and security.
- Have experience using Docker and Kubernetes to build and manage applications at scale.
- Understand probability, statistics, and common machine learning techniques.
- Communicate effectively with technical teams and non-technical stakeholders.
- Be comfortable owning scope and delivering solutions in a fast-paced environment.
Benefits
- The company is open to conversations about part-time hours.
- Applications are encouraged from candidates of all backgrounds, and every application is reviewed by a human.
- Interview candidates may opt out of the Metaview AI note-taker.
Tech Stack
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