Top Machine Learning Jobs in Sydney

As a Software Engineer Intern, you'll create tools for trading strategies, develop research platforms, and collaborate in small teams.

Design, develop, and deploy software solutions for automated trading systems while collaborating with researchers on technology priorities.

Lead and conduct cutting-edge ML research in Code LLMs, Reasoning Models, Agentic Systems, and Reinforcement Learning. Publish top-tier papers, collaborate with engineering teams to translate research into database product solutions, and mentor intern researchers.

11-week PhD internship developing, back-testing and implementing quantitative trading strategies. Build and improve mathematical models, translate algorithms into code, analyze unconventional data sources, and deploy signals in live trading while collaborating with senior researchers.

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.

The Manager, ML Engagement Management leads AI deployment processes, technical workshops, and drives customer engagement while ensuring project success and process improvements.

Support development and backtesting of quantitative trading strategies: translate models to code, analyze data (including unconventional sources), and implement/monitor trading signals in live environments under senior mentorship.

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.

The Manager of Cybersecurity Products will drive growth by developing strategies, managing the product portfolio, and executing product enhancements across the ANZ region.

As a Senior Software Engineer, you will design and implement features focused on digital twins, API development, and engineering simulations. You'll enhance algorithms, improve monitoring, and create tools for efficient data extraction and network design viability assessments.

Advise senior stakeholders to define and execute enterprise AI strategies, prioritise use cases, design operating models and governance, build business cases, lead transformation and consulting teams, and drive adoption to realise measurable AI-driven business value.

Lead AI strategy and transformation by identifying high-value AI opportunities, defining roadmaps, operating models, governance, and business cases; facilitate stakeholder workshops, enable adoption through change management and capability uplift, and measure value realisation.

The Senior Data Scientist will enhance survey operations, analyze data quality, run experiments, and collaborate with cross-functional teams to solve business problems using advanced data science techniques.

As a Data Scientist at Tracksuit, you will scale survey operations, apply statistical techniques, build data quality systems, and collaborate with product teams to develop brand measurement solutions.

Partner with clients to translate business goals into secure, scalable AI and data solution architectures. Design integrations, data flows, APIs, and governance-aligned architectures; facilitate workshops; produce artefacts and guide delivery teams.

Partner with business leaders to translate complex problems into analytical frameworks, deliver data-driven insights and visualisations, lead end-to-end analytical projects, and manage a team to improve portfolio performance and strategic decision-making.

Lead end-to-end product roadmaps for physics-enabled digital twin products, align cross-functional teams, translate customer needs into commercial product bets, build KPI and economic models to measure impact, mentor PMs, and drive platform or applications strategy to scale utility-facing solutions.

Lead product strategy and execution for content safety tools and services. Partner with engineering, data science, operations, legal, and policy to define safety outcomes, prioritise backlog, drive adoption, and operationalise review tooling, policy enforcement, UX, and moderator wellbeing. Act as escalation point for incidents, appeals, and investigations, and translate multi-stakeholder needs into measurable, defensible safety solutions.

Lead Lumi's automated credit decisioning function, owning decisioning strategy, scorecard calibration, model governance, performance monitoring, and cross-functional delivery. Manage a specialist team to design and deploy AI/ML-driven decision systems, ensure regulatory compliance, and align automated risk parameters with commercial objectives and portfolio health.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

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.

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 a Data Analyst team to analyze PB-scale transactional and customer data, build algorithmic systems and visualizations, implement ML/LLM solutions for compliance use cases, support business stakeholders with data requests, and translate findings into actionable recommendations.

Design, develop, and manage large-scale search and content recommendation systems. Apply ML-based personalization to improve content matching and distribution. Lead core recommendation module development, define success metrics, and collaborate with content, product, and business teams to drive AI product upgrades and better user and business outcomes.