Top Machine Learning Jobs in Melbourne

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

The Senior Account Executive will develop sales strategies, cultivate relationships with clients, and manage the sales process to close deals with banks and fintechs.

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

As a Strategic Sales Director, you will lead sales efforts, develop relationships with key executives, and drive significant transactions in Australia.

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.

Design and deliver enterprise-scale AI/ML solutions and architectures. Build production-ready systems using Azure AI stack, LLMs, agent frameworks, AKS, and memory stores; engage technical and business stakeholders to operationalise optimisation, edge, and agentic AI capabilities.

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.

As a Machine Learning Engineer, develop ML models for computer vision, integrate with products, manage data and experiments, and work on end-to-end ML operations.

The Lead Metallurgist will oversee resource evaluation, audit geometallurgy models, liaise with teams, ensure quality control, and mentor junior staff.

The Lead Metallurgist will oversee mineral resource evaluation, ensure quality control, audit geometallurgical models, and provide technical leadership, focusing on optimizing mine operations through advanced modeling and collaboration with teams.

The Director of Business Development will lead business development and go-to-market initiatives in mining, leveraging industry connections to establish executive relationships and create opportunities for Stratum AI's solutions. Key responsibilities include market development, sales strategy creation, and pipeline development, targeting high-value clients and navigating complex sales environments.

As a Senior MLOps Engineer, you will enhance ML operations by designing and maintaining infrastructure, implementing CI/CD pipelines, and collaborating with data scientists to streamline workflows.

Unpaid, part-time internship offering hands-on mentorship in robot learning and imitation learning. Work ranges from setting up robot simulation frameworks, robot integration and human demonstration data collection, to designing and training ML algorithms and deploying models on robots. Remote theoretical work allowed; Sydney-based preferred for hardware testing.

Execute end-to-end outbound CRM campaigns (email, SMS, push): audience segmentation, QA, build, deploy and optimize lifecycle programs. Use automation, A/B and multivariate testing, machine learning/predictive modeling, and analytics to improve conversion and LTV. Collaborate with Data & Analytics, MarTech, product, media, and agencies to meet performance goals and extract insights for template and strategy optimization.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

Design, develop and optimise foundation-model and self-supervised learning solutions for healthcare. Build and validate ML training pipelines, evaluate generative models, collaborate with engineering/devops teams, document progress, and apply software engineering best practices for production-ready AI-as-a-medical-device products.

Lead design and delivery of production-scale AI/ML products and platforms. Architect, build, deploy, monitor and improve ML systems (including LLMs, retrieval, ranking and generative AI). Drive ML lifecycle practices, data/feature foundations, evaluation frameworks and MLOps using Python, SQL and modern ML tools. Mentor engineers, set technical direction, ensure ethical, reliable, and scalable AI capabilities aligned to product priorities.

One-year, full-time fellowship supporting design, delivery, and evaluation of interventions for smallholder farmers. Duties include research and analysis, pilot design, field implementation, M&E, and cross-team collaboration with heavy mentorship and rotating in-country placements.

Design and deploy AI/ML solutions on Snowflake, build POCs and pipelines using SQL/Python and partner tools, advise customers and integrators, enable best practices, and collaborate with product and engineering teams.

Design and implement robust, large-scale distributed ML training systems optimized for low-bandwidth, high-latency environments. Build model-parallel training strategies, checkpointing and recovery, GPU and memory optimizations, P2P networking, NAT traversal, and monitoring to ensure resilient, efficient multi-participant training.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

Design, build and deploy ML models and production ML services (real-time and batch), develop MLOps pipelines, feature engineering, LLM and generative AI applications, monitor and optimise models, and collaborate cross-functionally to deliver measurable business impact.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

The Senior Machine Learning Engineer will design, train, and deploy ML models for optimizing revenue in advertising, taking ownership of product development and leading the ML discipline.