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Senior Machine Learning Engineer - Agent Tools Interop (AU remote)

SeniorFull-timeRemoteMelbourne VIC, AustraliaPosted 2 months agoVerified 2 months ago
Pending fitX of Y criteria met

About the job

This job is about being a Senior Machine Learning Engineer on the Agent Tools Interop team, where you'll work on making tool calling reliable, safe, and scalable across Canva's ecosystem. Your contributions will empower teams to build agentic features, creating a shared foundation for AI integrations. The team values collaboration and innovation, ensuring that every member can thrive in a flexible work environment.

Meet the team

About the company

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You'll be responsible for

🔧

Building systems

Building and evolving the systems that enable agents to discover, invoke, and safely execute capabilities across Canva at scale.
📐

Designing tool schemas

Designing tool schemas and definition patterns that maximize LLM tool selection accuracy and reliable invocation across diverse agent consumers and AI integrations.
🌐

Collaborating with teams

Collaborating with product, platform, and GenAI teams to integrate agentic capabilities into production systems and understand tool use behaviors at real-world scale.

Key criteria

🛠️

Hands-on experience with LLM tool use

Proven experience designing tool schemas and shipping integrations.

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📊

Evaluation framework expertise

Experience building systems to measure AI feature quality.

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💻

Java proficiency

Strong background in Java for backend services infrastructure.

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Think you're a good fit?See what the hiring team are looking for

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5 criteria for this job
Hands-on experience with LLM tool use
Proven experience designing tool schemas and shipping integrations.

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Evaluation framework expertise
Experience building systems to measure AI feature quality.

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Java proficiency
Strong background in Java for backend services infrastructure.

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Collaboration with engineering teams
Experience working with backend or infrastructure teams for AI integrations.

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Familiarity with agent frameworks
Knowledge of MCP, LangChain, or similar frameworks is a plus.

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A meaningful career starts with a match

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