Top AI Jobs in Melbourne

Lead and scale an AI Foundry pre-sales team to deliver high-velocity POCs and accelerators across ServiceNow Platform AI & Data. Operationalize POC processes, ensure architectural quality, mentor architects and engineers, partner with sales, and drive reusable technical assets to increase adoption and revenue.

The Research Assistant will conduct research on carbon neutral infrastructure, including carbon assessment, structural engineering, and AI applications. They will collaborate with teams, produce technical manuals, and support industry partnerships.

The Solution Sales Executive will drive sales of FICO's platform in financial services, engaging with clients, managing relationships, and collaborating with internal teams to deliver solutions.

The Clinical Development Analyst specializes in developing and managing Computer-Assisted Coding for healthcare, ensuring alignment with coding standards and compliance, and providing clinical expertise in coding development.

The Content Solutions Engineer will act as a subject matter expert in AI and Machine Translation, providing pre-sales support, technical consulting, and collaborating on solution architecture to help clients optimize globalization processes.

Join CommBank's Data Science & AI Talent Community to build AI solutions improving customer outcomes while fostering responsible and ethical use of AI. Positions available range from Data Scientist to Principal Data Scientist, emphasizing collaboration and innovation in a flexible work environment.

The Reserve Engineer maintains and services robotic hardware, responds to failures at client sites, and ensures customer satisfaction. Responsibilities include learning hardware, communicating repairs, and assisting with deployment projects.

The Partner Development Executive builds relationships with strategic partners to align SUSE solutions with objectives, drive pipeline and business growth, and enhance SUSE's market presence.

As a Senior Engineer, you'll develop AI workflows, lead delivery of AI agents, and integrate systems while collaborating with business teams to automate processes.

The Business Development Manager will onboard new sellers, build relationships, conduct market research, negotiate contracts, and collaborate with internal teams.

The role involves being a technical advisor, focusing on AI solutions within GitLab's DevSecOps platform, guiding strategy and value for customers, and leading technical evaluations and workshops.

Promote Lilly's cardiometabolic health products, build relationships with healthcare professionals, travel regionally, maintain customer satisfaction, and comply with standards.

Build and evolve the platform harness for agentic workflows: runtimes, tooling, governance, observability, and evaluation harnesses. Split time between building orchestration and reviewing/improving agent outputs, ensuring safe, reliable, repeatable customer-facing delivery.

Lead and support execution of ADI's global compliance programs: risk‑based monitoring, policy management, testing, investigations, training, ISO 37301 alignment, audits, remediation, and cross‑functional stakeholder coordination.

Support and enhance ADI's global compliance program aligned to enterprise risk and ISO 37301. Monitor regulatory developments, update policies, execute risk‑based monitoring and testing, manage investigations and remediation, support audits, develop training and communications, track metrics, and collaborate with Legal, HR, Finance, IT, and Operations to drive continuous improvement.

This role leads enterprise-scale AI and Data transformation programs, acting as a trusted advisor to senior executives, and shaping data strategies and governance frameworks.

The Professor will lead research in neuro-symbolic and trustworthy AI, engage in teaching and curriculum development, and foster national and global partnerships.

Lead end-to-end solution architecture for data, analytics and AI initiatives. Design scalable, secure cloud data platforms and AI solutions, embed governance and responsible AI, guide delivery teams, manage architectural risk and technical debt, and evolve enterprise data and AI architecture roadmaps and standards.

Lead AFCA's end-to-end data and AI governance, designing frameworks, policies and assurance processes. Oversee data quality standards, AI evaluation (accuracy, bias, reliability), inventories of approved tools, and cross-functional governance forums. Integrate governance with privacy, information management and security, monitor regulatory developments, and coach the data governance team to embed responsible AI practices across the organisation.

Lead product strategy and execution for AI and personalisation initiatives. Define vision, prioritise experiments, optimise channel performance, and drive measurable commercial growth through cross-functional collaboration, data-driven decisions, and stakeholder influence.

Lead net-new enterprise sales within Banking & Financial Services by owning full sales cycles, developing territory and pipeline, co-selling with hyperscalers and partners, and positioning Iron Mountains digital portfolio (AI, intelligent document processing, workflow automation) to deliver measurable ROI and close high-value deals.

Design, build, and deploy end-to-end AI solutions using H2O.ai platform, including predictive ML, GenAI/LLM and agentic systems. Work on data preparation, feature engineering, model training, evaluation, deployment, monitoring, backend services/APIs, and customer implementations. Support demos and technical workshops and collaborate with cross-functional teams to deliver production-ready AI features and measurable business outcomes.

Design, build, and deploy production-grade AI applications and agentic systems. Own end-to-end AI solutions including data preparation, feature engineering, model development, deployment, monitoring, and governance. Architect GenAI systems (RAG, LLMs/SLMs, agents), build backend services/APIs, guide customers on adoption and responsible AI, and deliver technical enablement.

Lead design and delivery of scalable data and AI platforms across Azure and Databricks. Architect production-grade ML/LLM solutions (RAG, agentic patterns), build batch and streaming pipelines, formalize medallion/lakehouse standards, implement MLOps/DataOps (CI/CD, monitoring, orchestration), embed Responsible AI and governance, and provide technical leadership, mentoring, and cross-functional delivery.

The AI Engineer will design, develop, and deploy AI/ML solutions using AWS and/or Azure, build data pipelines, and maintain ML workflows while collaborating with teams to address business challenges.