Top Machine Learning Jobs in Sydney

The Principal, Information Governance Advisor will drive business growth, manage high-impact engagements, and mentor junior consultants, focusing on information governance solutions.

As a Senior Machine Learning Engineer, develop ML models to digitize infrastructure from varied data sources while optimizing training pipelines and mentoring junior engineers.

Develop next-gen quantum magnetometers, enhancing their sensitivity and robustness using quantum control algorithms, statistical techniques, and digital signal processing.

This role involves research and development on quantum sensors, creating control solutions and sensor fusion algorithms, analyzing performance, and collaborating with teams to push boundaries in quantum technology.

Lead AI-driven transformation in investment platforms, deliver scalable solutions, optimize processes, and mentor junior analysts to enhance business efficiency.

The role involves driving new enterprise sales, managing customer discussions about AI solutions, and closing $500k+ deals while collaborating with sales teams.

The role involves driving net-new sales and recurring revenue for IFS's AI solutions, engaging with executives, and leveraging industry expertise to close large enterprise AI deals.

Design and build ML infrastructure, influence data access and model deployment, partner with researchers to optimize ML models for trading, and mentor engineers.

The Key Account Manager will cultivate client relationships, drive sales goals, and manage strategic accounts in the financial services sector, focusing on AI-driven fraud solutions.

The Senior Data Scientist will lead the development of machine learning models, conduct data analysis, and collaborate with cross-functional teams to optimize services and tools at Mable.

Develop trading strategies using statistical and machine learning algorithms, optimize low latency strategies, and analyze market behavior at Akuna Capital.

Lead the AI strategy and team at EML, overseeing project delivery and ensuring adherence to best practices in AI governance.

The Sales Account Executive will drive revenue growth by selling AspenTech software and services, managing accounts, and building relationships in the Mining sector.

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.

The Technology Risk Manager will develop risk frameworks, embed risk practices, report on risk to management, and lead controls automation in a financial services context.

As a Senior Data Scientist, you'll lead data science projects, supervise teams, ensure model quality, and apply statistical methods for insights from Nearmap imagery data.

As a Machine Learning & AI Engineer, you will design, build, and deploy scalable data solutions using SQL and cloud platforms, support ML workloads, and communicate with stakeholders.

Design and manage large-scale SaaS and cloud services, providing technical leadership and improving engineering practices, with a focus on user experience.

The role involves working as a Senior Data Engineer focusing on data engineering and machine learning. Responsibilities include building ML models, data processing, and stakeholder engagement, primarily for banking clients.

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 AI/ML Architect will design and architect AI solutions, collaborate with teams, and support customer adoption of Snowflake's AI/ML technologies, while showcasing technical expertise in sessions and content production.

As an AI/ML Engineer, you will develop and optimize AI solutions for renewable energy assets, collaborating with a skilled team to deploy algorithms in real-world projects.

As a Senior ML Engineer, you will operationalize ML models, design scalable MLOps infrastructure, build feature stores, automate workflows, and ensure model monitoring, collaborating with data scientists and engineers.

As a Machine Learning Engineer, you will implement and optimize decentralized training systems for AI models, focusing on distributed training, performance optimization, and deployment of sharded models.

The role involves developing deep learning models for computer vision applications, collaborating with a team, optimizing models, and ensuring code quality.