Top Machine Learning Jobs in Melbourne

Lead frontier research in on-device AI, focusing on inference efficiency, model routing, autonomous research pipelines, and real-world evaluations. The role owns significant parts of the research agenda and requires designing experiments, deriving actionable insights, and translating novel ideas into performance improvements. Work may include speculative decoding, quantization, distillation, reinforcement learning, accelerator optimization, and deployment under strict device constraints.

Graduate software engineers will contribute across any layer of Maincode’s production AI system, Matilda. Responsibilities may include supporting model training, inference, and infrastructure. Candidates should research the company and explain how they can contribute to building world-class Australian-made AI. Previous industry experience, including internships, is advantageous but not required.

Lead the evolution of customer onboarding and data conversion through AI, automation, AWS cloud services, and data intelligence. The role designs scalable automation, improves data quality, optimizes platforms and pipelines, develops predictive capabilities, and partners cross-functionally to reduce migration risk and improve customer outcomes.

Develop and deploy machine learning products and services by translating complex business problems into applied research programs. Build robust data pipelines and reusable code in Python or Scala, develop and evaluate applications involving NLP, computer vision, and LLMs, and monitor algorithms at scale. The role also involves managing research risks, collaborating cross-functionally, mentoring colleagues, communicating complex findings, and raising scientific and engineering standards.

Develop geophysical modeling capabilities for quantum sensing applications, including forward propagation models, potential field inversion, anomaly detection, simulation analysis, statistical assessment, and machine learning algorithms. The role involves building software for field data analysis, modeling underground systems, validating sensor applications, and optimizing surveying techniques in collaboration with geophysics and technology teams.

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.

Leads ML and platform engineering teams building scalable, production-grade machine learning infrastructure. Responsibilities include coaching engineers, guiding architecture and engineering trade-offs, improving MLOps maturity and observability, translating business goals into delivery plans, managing roadmaps, maintaining system health, and supporting production incidents through code review, debugging, or hands-on development. The role supports AI products including conversational GenAI, automated bank reconciliation, document capture, and cash-flow forecasting.

Lead end-to-end data science initiatives involving exploratory analysis, behavioral insights, experimentation, recommendation, ranking, personalization, and machine learning. Develop and productionize models, design offline and online evaluations, measure commercial impact, and establish rigorous modeling and documentation standards. Collaborate with Product, Data, Technology, and Commercial teams to solve complex customer problems and improve vehicle marketplace experiences.

Lead the design, development, deployment, and maintenance of scalable cloud-native platform capabilities for Walmart Connect’s sponsored search ad server. Build infrastructure, tooling, AI/ML frameworks, and distributed systems; conduct design reviews; drive software lifecycle activities; mentor engineers; influence architecture and technical decisions; and collaborate across teams to translate complex business needs into reliable, data-driven solutions.

Serve as a trusted technical advisor for AI and cloud infrastructure solutions. Partner with customers, sales teams, and technology partners to understand business needs, design architectures, lead workshops and technical evaluations, and deliver demonstrations. Translate AI strategies into scalable, secure deployments using modern infrastructure, cloud, networking, storage, GPU, container, and model-serving technologies. Present solutions to technical and executive audiences while supporting customer adoption and measurable outcomes.

Conduct independent research on frontier AI evaluation and auditing. Design rigorous evaluations, audit methods, and reproducible experimental pipelines; analyze model capabilities, risks, robustness, and alignment-relevant behavior. Produce audit reports, recommendations, publications, tools, and presentations while collaborating with technical, policy, engineering, and standards teams. The role requires careful handling of confidential information and may involve pilot audits with frontier AI companies.

Leads UniSuper’s data science capability and a specialist team delivering predictive models, machine learning, and advanced analytics. Sets technical standards, oversees model development and production maintenance, establishes governance, monitors performance and fairness, and translates analytical outputs into business decisions. Partners with senior stakeholders and Product Owners to identify valuable opportunities, prioritizes work, evaluates commercial and operational impact, and supports financial crime, efficiency, and regulatory objectives.

Leads commercial performance for global and regional eCommerce markets, improving revenue, margin, EBIT, conversion, AOV, demand shaping, customer experience, and retention. Partners with market leaders to diagnose performance, recommend actions, align improvement plans, govern KPI frameworks, and ensure adoption. Leads data storytellers, establishes analytical and measurement standards, develops global playbooks, and influences senior stakeholders across a global matrix organization.

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.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

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.

Develop machine learning and deep learning models that digitize electricity infrastructure from LiDAR, imagery, GIS, and vector data. Build scalable training, serving, QA, and monitoring pipelines; identify data and distribution drift; improve model deployment speed; and apply MLOps best practices. The role also involves defining ML strategies, solving ambiguous problems, collaborating asynchronously across functions, and mentoring junior engineers.

Design, model, optimise, prototype, align, and characterise optical and electro-optical imaging systems for autonomous sensing platforms. Responsibilities include optical tolerancing, sensitivity analysis, stray-light and ghost analysis, component selection, optomechanical integration, image-quality optimisation, manufacturing transition, and collaboration with machine-learning and computer-vision teams. The role requires hands-on optical engineering experience and eligibility for an Australian Defence security clearance.

Leads analysis, mining, modeling, and visualization of large-scale transactional, operational, and customer data. Partners with compliance teams to prioritize analytical use cases, support regulatory requirements, improve business efficiency, and translate complex findings into actionable recommendations. Oversees multidisciplinary analysts, manages stakeholder data requests, assesses business changes, and develops analytical systems using machine learning, big data technologies, and visualization tools.

Own end-to-end implementation delivery for multiple enterprise utility customers, from contract signature through go-live, hypercare, and handover to Customer Success. Coordinate cross-functional internal teams and customer stakeholders, manage scope, milestones, dependencies, risks, resources, and change, and provide executive updates. Improve implementation processes, tooling, templates, and playbooks while reducing time to customer value.

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.

Lead ClickUp’s APJ revenue strategy, initially focusing on building direct commercial and enterprise sales across Australia and New Zealand while supporting channel-led growth across Southeast Asia. Responsibilities include recruiting and developing sales teams, managing enterprise accounts, driving partner collaboration, forecasting pipeline, owning ARR targets, developing territory strategies, and engaging senior customer and partner executives.

Owns high-impact ANZ strategic projects spanning commercial growth, customer expansion, partnerships, sales, and delivery. The role translates regional priorities into workstreams, milestones, dashboards, operating cadences, and repeatable playbooks. It resolves cross-functional blockers, improves sales-to-delivery execution, supports priority accounts and partners, and uses data, automation, and AI to improve regional performance. Success is measured through revenue retention, opportunity progression, partner contribution, delivery efficiency, and stronger operating leverage for regional leadership.

Build and optimize an on-device AI inference stack, including custom inference engines, GPU kernels, serving runtimes, model routing, continuous batching, and decoding strategies. Develop C++ systems for low-latency inference across Apple, NVIDIA, AMD, Snapdragon, and other platforms. Profile performance, optimize memory and compute bottlenecks, and translate ML research into production infrastructure.

Own the end-to-end finance and accounting function across entities and jurisdictions. Responsibilities include financial close, consolidations, reporting, cash management, compliance, tax, audits, external partners, finance systems, controls, automation, budgeting, forecasting, fundraising support, and team leadership. The role will build scalable finance infrastructure, improve operational processes, provide decision support to executives and investors, and ensure accurate, timely, and reliable financial information.