Top Machine Learning Jobs in Melbourne

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.

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.

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.

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.

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.

Build, evaluate, and ship machine-learning ranking and relevance systems for private, team, and brand content search. Improve relevance, recall, result understanding, search recovery, and exact-title matching. Contribute to Elasticsearch, OpenSearch, vector search, indexing, annotation, and agent-driven search. Investigate production regressions, run experiments, measure search-quality impact, own scoped projects end to end, and communicate technical trade-offs across technical and nontechnical stakeholders.

Hunts for new-logo enterprise sales opportunities for IFS AI solutions, builds strategic-account pipeline, leads consultative executive discussions, and closes complex $500,000+ ACV deals. The role requires positioning AI value, partnering with regional and solution teams, engaging multiple stakeholders, and applying industry expertise across sectors such as manufacturing, aerospace, energy, construction, and telecom.

Build and deliver production-grade generative AI and LLM applications using Python, machine learning, cloud platforms, APIs, SQL, and data pipelines. Contribute to AI evaluation, observability, testing, code reviews, and technical standards. Collaborate with clients and domain experts to define solutions, explain technical concepts, and communicate risks and trade-offs. The role supports end-to-end AI/ML delivery while developing technical and consultative expertise.

Develop and deploy credit risk, IFRS 9 provisioning, forecasting, stress-testing, and emerging-risk models. Responsibilities include sourcing and validating data, researching explainable modeling techniques, monitoring model performance, maintaining governance standards, conducting ad hoc analytics, and communicating insights to business stakeholders. The role requires collaboration, commercial acumen, timely delivery, and familiarity with traditional statistical models, machine learning, AI tools, and the consumer credit lifecycle.

Serves as the primary technical and customer support contact for complex Azure issues and projects. Troubleshoots mission-critical applications, conducts health checks and root-cause analysis, manages escalations, advises on Azure configurations and deployments, and communicates technical issues to varied audiences. Synthesizes customer feedback, identifies product and knowledge gaps, advocates for platform improvements, and partners with engineering, product, field, and support teams to improve reliability and customer experience.

Evaluate AI model outputs on data science, statistics, machine learning, experimentation, and quantitative problems. Develop expert prompts, datasets, and reference solutions; identify statistical and methodological errors; and provide structured feedback to improve model performance. The role requires Python, machine learning, statistics, data analysis, experimentation, Pandas, and data modeling skills.

Develop threat models, statistical verification algorithms, calibrated tests, and production verification services for decentralized training and inference on untrusted heterogeneous hardware. The role focuses on detecting incorrect model outputs, malicious training behavior, free-riding, poisoning, data extraction, and reward manipulation while controlling false positives and negatives. Candidates need deep statistics and probability expertise, experience shipping or publishing calibrated decision systems, and familiarity with statistical testing, re-execution, cryptographic proofs, and trusted hardware.

Lead end-to-end UX and product design for Timescapes’ construction progress tracking platform. Research customer needs, prototype and test solutions, iterate throughout the product lifecycle, and design complex AI-powered capabilities. Collaborate with customers, product managers, and engineers while helping expand the design system, introduce AI-assisted workflows, and develop concepts for future products.

Develop and deploy machine learning models that improve e-commerce search relevance, recommendations, product classification, and customer intent understanding. Responsibilities include collecting and preparing large datasets, feature engineering, predictive modeling, validation, testing, and leading work in areas such as NLP, computer vision, information retrieval, and deep learning. The role requires building scalable, reusable machine learning pipelines and collaborating across concurrent projects.

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.

Customer-facing threat analyst supporting financial institution customers with fraud detection, prevention, and behavioral biometrics solutions. Responsibilities include advanced analytics, fraud strategy consulting, customer education, rule deployment for attacks, proof-of-value analysis, performance reporting, threat research, and sales enablement. The role partners with customers, Data Science, Sales, and Product teams while addressing account takeover, scams, account opening, and mule detection.

Design, implement, and maintain Abi’s production autonomy stack, including path planning, SLAM, collision avoidance, perception integration, simulation, and safety mechanisms. Harden software and integrated hardware systems through testing and validation, support a deployed robot fleet, debug sensors and effectors, improve deployment processes and user experience, and contribute to systems engineering across the product lifecycle. Lead cross-functional technical discussions and perform customer site visits for testing and feature validation.

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.

Provides advanced statistical expertise to technical operations, manufacturing, quality, and regulatory teams in a GxP environment. Applies statistical modeling, multivariate analysis, machine learning, process monitoring, comparability assessments, and analytics to support product quality, investigations, validation, lifecycle management, technology transfers, and continuous improvement. Also supports regulatory submissions, audits, training, and cross-functional decision-making through evidence-based recommendations.

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.

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.

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

Manage sprint and release planning for Mosaic, translate business needs into a prioritised backlog, guide engineering and data science teams, define acceptance criteria, support UAT and incident triage, and coordinate compliance and operational commitments to deliver energy trading optimisation features.