Top AI Jobs in Melbourne

Design, build and scale production-ready AI capabilities and applications using Python and modern cloud tech. Collaborate with cross-functional teams to deliver secure, observable, and responsible AI solutions, mentor engineers, drive architecture decisions, and ensure operational excellence across AI platforms.

Lead client engagements to design and implement practical AI governance frameworks, assess AI use cases for risk and compliance, embed governance into AI solution design, facilitate stakeholder workshops, and develop governance artefacts to enable responsible, scalable AI adoption.

Design, build and maintain automation and AI/LLM integrations to reduce manual work, improve accuracy and security, connect business systems, create dashboards, and enforce governance, documentation and testing so tools are reliable and auditable.

As an AI Consulting Solutions Engineer, you'll lead pre-sales efforts for Netskope's AI Security products, assist sales teams, engage customers, and collaborate with product management.

The AI Platform Engineer leads the development of production AI agents and components, collaborates on AI implementations, and maintains AI systems for reliability and observability.

Manage full customer lifecycle for multi-location Auto accounts: lead onboarding, drive product adoption and retention, manage health scores and risk, build stakeholder relationships, coordinate cross-functional teams, and act as product expert to deliver measurable customer outcomes.

Lead generative AI image production for realistic personas and models. Build and optimize scalable generative pipelines, automate batch workflows, evaluate new models/tools, define technical direction and best practices, and improve image quality, consistency, speed, and cost-efficiency.

Design and operate advanced AI infrastructure, focusing on GPU clusters and large-scale systems. Collaborate with researchers and develop architectural solutions from first principles.

The role involves building and maintaining back end services for a large language model, focusing on APIs, infrastructure, reliability, and system performance.

Design and ship agentic AI features: build stateful multi-turn conversational systems, memory and context graphs, RAG and hybrid search, data pipelines and integrations, production LLM evaluation and observability, prompt engineering, safety guardrails, and partner with product and people science to deliver scalable, responsible AI in production.

Lead end-to-end implementation of integration solutions using MuleSoft Anypoint Platform. Work with solution architects, design, develop, test and deploy APIs and event-driven integrations (Solace/Kafka/Anypoint MQ). Apply API-led connectivity, RAML/Swagger, SOA/ESB and microservices patterns. Drive technical and commercial discussions, follow DevOps/CI-CD practices, mentor team members and maintain MuleSoft certification.

Lead client-facing AI adoption programmes end-to-end: design change strategies, build executive sponsorship and champion networks, measure behaviour change and ROI, run executive workshops and company-wide engagement, codify playbooks, and drive renewal and expansion through sustained adoption.

Lead company-wide AI adoption by selecting tools, running workshops, diagnosing team problems, building reusable workflows/automation, tracking tool usage and license ROI, and writing responsible-use guidelines while partnering across Creative, Marketing, Technology, Finance and People teams.

Support legal operations by reviewing workflows, designing AI-enabled solutions, building prompt libraries and SOPs, testing tools (Copilot, ChatGPT, Claude), assisting contract review, regulatory tracking, preparing board/committee materials, and training colleagues on automation and workflows.

Lead enterprise AI adoption across client-facing teams: act as SME for ChatGPT/Claude/Copilot/AskDex, build use-case library, run user community, create AI agents and workflows, measure adoption and impact, and ensure alignment with governance, risk and responsible AI standards while reporting to executive leadership.

Build and operate .NET/Python microservices and secure REST APIs on AWS to deliver agentic AI features for risk management. Contribute to architecture, CI/CD (GitHub Actions, ArgoCD), observability (Grafana/Prometheus), and integration with LLMs, event streams, and data products while ensuring security and compliance.

Lead the design vision for AI-first product experiences, shaping UX/UI, service patterns, and ethical use of AI. Drive strategic design projects, coach teams, partner with Product, Engineering, Brand and Research, and communicate vision to executives to deliver cohesive, data-driven, generative and conversational experiences.

Define safety, usability, and performance metrics for AI and robotic products; translate VLA and agentic RAG breakthroughs into customer value; engage enterprise adopters for feedback; lead cross-functional teams; own product roadmap and delivery for agentic and robotic deployments.

Design, deploy, and maintain MLOps infrastructure: manage model registries, continuous training loops, and A/B testing. Deploy agentic systems as scalable microservices on Kubernetes and build observability dashboards tracking token usage, latency, and agent reasoning.

Design and optimize multimodal AI systems integrating vision and audio models. Improve voice-to-voice streaming latency, embed vision encoders and audio-native models into agent reasoning, and architect multimodal RAG systems for retrieving insights from videos and PDFs.

Develop and train foundation models for robotics, align text-based reasoning with low-level control policies, design and run zero-shot generalization experiments, collaborate with interdisciplinary teams, and present research findings at conferences.

Design and implement multi-agent orchestration frameworks, build tool-calling pipelines and reasoning loops, and optimize latency and token usage for real-time agentic workflows.

Optimize and compress large language and vision models for on-device inference. Develop distillation and hardware-specific compilation pipelines, deploy models to edge devices, and benchmark performance across NPU/GPU architectures to ensure efficient on-device operation.

Design and implement HRI systems: build intent-recognition models from gaze, gesture, and voice; create socially aware navigation algorithms; and design visual and auditory robot feedback and interfaces. Run user studies and prototype AI-driven voice and visual interfaces to validate interaction paradigms.

Own end-to-end Instagram Reels production: ideation, scripting, editing, and delivery. Use AI tools to support ideation and production, test formats, optimize for retention, and stay on top of short-form video trends to grow international audiences.