Top Machine Learning Jobs in Melbourne

Design and implement novel real-time computer vision algorithms in C++, develop and maintain C++ CV pipelines for autonomous systems, integrate deep learning models with perception systems, collaborate with AI/robotics/optical engineers, and keep up with academic research to deliver reliable edge solutions.

Serve as the product specialist for Zero Trust Networking across Australia and New Zealand, driving adoption and revenue for ZTNA, SD-WAN, and branch solutions. Collaborate with solution engineers and account teams to gather requirements, create value propositions, close deals, implement account-based strategies, and expand partner and customer relationships. Operate in a hybrid model (Sydney/Melbourne) and travel extensively as needed.

Design, implement, and integrate real-time computer vision algorithms into high-performance C++ pipelines for edge-deployed autonomous systems. Focus on custom perception capabilities, model adaptation and evaluation, inference optimization, dataset curation, and cross-functional integration with AI, robotics, and optical teams to deliver robust mission-capable solutions.

Lead and mentor engineers to design, build, and maintain scalable automation and onboarding systems. Implement AI/data-driven risk detection, collaborate with product/ops/compliance, drive architecture and reliability, and improve operational efficiency.

Support Emiri client deployments by bridging product support, UX, and development: investigate issues, triage root causes, configure and QA client models, coach commercial teams, test fixes, and communicate feedback to product. Use Jira/Confluence and apply NLP/ML knowledge to improve processes and user education.

Provide transactional legal support on private equity, M&A, and financing deals by reviewing, drafting, and negotiating NDAs and ancillary documents using client playbooks and an AI-enabled platform. Manage workload across concurrent transactions, identify deviations, apply fallback language per client guidance, collaborate with global legal, product, and engineering teams, and help improve internal processes and AI tools.

Lead the superannuation and wealth portfolio, ensuring commercial and delivery success of client engagements. Build C-suite relationships, drive business development, shape AI-driven propositions, manage proposals/pricing, and grow a high-calibre team while implementing AI-enhanced analytics solutions.

Lead and embed Computational Design across projects and regions by developing workflows, automation, and AI-enabled tools. Provide technical leadership, mentor specialists, coordinate resources, create standards and training, collaborate with BIM/Sustainability/IT, and represent the practice in industry engagement and research.

The Genesys Cloud Architect will lead the design and architecture of cloud-based contact center solutions, ensuring alignment with business strategies and technical requirements.

Design and implement end-to-end data solutions: build data pipelines, perform data modelling and warehousing, implement ETL, write scalable Python/SQL/Spark code, work with cloud data services, support ML/AI initiatives, and liaise with clients to deliver practical, secure data products and visualisations.

Lead design and implementation of AI research and production infrastructure. Mentor junior engineers, and collaborate to enhance data usability, solving complex technical challenges.

Lead and execute Dataminr's Defence sales strategy across APAC: build strategic customer relationships, drive revenue growth, manage procurement and sales cycles, partner with cross-functional teams, mentor sales teams, and maintain accurate pipeline and forecasting in Salesforce.

Lead design and implementation of AFCA's AI governance and assurance framework. Establish AI lifecycle assurance, conduct technical risk assessments, define governance standards and evaluation methods, maintain AI inventory and risk register, report to executives, and uplift organisation-wide AI governance capability.

Partner with sales and cross-functional teams to win deals by designing and demonstrating Snowflake-based data and AI solutions. Lead discovery, workshops, proofs-of-concept, and technical presentations; translate business needs into architecture and implementation patterns; build trusted relationships with technical and executive stakeholders to drive adoption and long-term value.

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.

Hands-on principal engineer responsible for full-stack development (frontend, APIs, authentication/security), cloud deployments on Azure (including AKS and deployment pipelines), Node.js/JVM/Python development, AI-assisted coding, testing (e.g., Playwright), API documentation (Swagger), package management (NPM), and working with machine learning components. Requires hybrid onsite presence.

Lead a multidisciplinary engineering team building next-generation conversational and semantic search capabilities. Drive technical direction, delivery, operational excellence, LLM integration, evaluation-driven development, and cross-functional collaboration to scale AI-powered search systems.

Lead the FICO–Accenture alliance in ANZ to grow ARR and CoE through consultative selling, joint value propositions, pipeline management, co-marketing, and end-to-end deal execution. Build executive relationships, productize repeatable IP, oversee joint business plans, and drive revenue via channel and direct sales while representing FICO at industry events.

As a Senior Software Engineer, you'll design and implement features related to digital twins, data abstractions, and structural analysis, leveraging machine learning and algorithms.

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.

Lead enhancement of risk infrastructure and automation, analyze historical trading data, administer MT4/MT5 and third-party trading tech, collaborate on hedging and mitigation strategies, prepare reports for Head of Risk, and mentor team members.

Design and implement large-scale, production-grade distributed systems to power generative AI features. Own architecture, operational reliability, and technical debt. Collaborate with applied scientists to productionize ML/LLM models, mentor engineers, and improve data usability and engineering standards.

Lead strategy and execution for fraud risk management across the platform. Develop detection and prevention frameworks, optimize transaction screening, partner with Compliance, Data Science, Engineering and Product, oversee KPIs and vendor costs, lead a risk strategy team, and pilot AI/LLM-driven tools to enhance detection while enabling business growth and regulatory alignment.

Lead design and implementation of large-scale distributed production systems powering generative AI features. Own architecture, mentor engineers, manage technical debt, operationalize ML/LLM models, and collaborate with scientists to productionize research using Python, SQL, Spark/Dask, AWS, and Kubernetes.

The Research Scientist will tackle advanced research problems in Protocol Learning, publish findings, and work collaboratively in a distributed model training environment.