Top Machine Learning Jobs in Sydney

The AI Deployment Manager will lead strategic implementations of AI solutions, ensuring customer satisfaction through exceptional onboarding and change management to drive adoption and measurable success.

Lead a team of Data Scientists focused on credit decisioning, collaborate with leadership teams, and implement operational frameworks to scale.

Develop customer-facing automation solutions, contributing to design, coding, and troubleshooting, while collaborating with stakeholders on technical issues.

The Research Engineer role involves supporting ML training infrastructure, building tools, and managing varied engineering tasks. Candidates should demonstrate initiative and readiness to learn.

The Senior Account Executive is responsible for driving sales efforts in financial crime solutions, building relationships, achieving revenue targets, and creating new business opportunities.

The Principal Product Manager leads product lifecycle management for brand safety solutions using ML/AI, ensuring effective collaboration and communication across teams.

Deliver compelling presentations and host discussions on emerging AI topics, engaging with senior leaders to translate AI concepts into strategic insights.

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

The Product Manager will create innovative data products for banks and fintechs while ensuring compliance with regulations and enhancing client experiences using machine learning and analytics.

The General Manager will lead business development, forge strategic partnerships, and drive growth in the renewable energy sector, focusing on battery storage solutions.

The role focuses on enterprise sales of AI solutions, targeting new accounts and driving significant revenue by engaging with customers and leveraging industry knowledge.

Solution Consultant leading product demonstrations and strategic discussions for Workday's recruiting solutions, focusing on improving candidate experiences and aligning client goals with technology offerings.

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

Seeking a Senior Recruiter to drive recruitment in the APJ region for GTM growth, utilizing data-driven strategies to identify and engage top talent while building talent pipelines and enhancing diversity in hiring.

Lead the definition and delivery of AI-driven features and solutions. Translate complex needs into clear requirements, prioritize use cases, and coordinate cross-functional teams to deliver effectively.

Lead the Reporting and Data Analysts, implementing scalable reporting solutions, driving data-driven decision-making, and enhancing operational reporting and analytics across the organization.

The Customer Technology Advisor will leverage technical expertise in Data and AI to enhance customer relations, design solutions, and lead pre-sales processes, ensuring alignment with client needs and Kyndryl standards.

Lead and mentor a remote engineering team for Cashalo, driving performance, improving delivery processes, and collaborating with leadership on strategic initiatives.

The Fraud Risk Manager will design and oversee UR's fraud prevention program, manage fraud monitoring, investigations, and implement a governance model. Responsibilities include optimizing recovery workflows, maintaining compliance documentation, and reporting insights to stakeholders.

Develop and design learning paths and courses in various technical domains, authoring materials and assessments while collaborating with team members.

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

Lead the development and deployment of AI and ML solutions, oversee MLOps strategy, and collaborate with data scientists to enhance data-driven products.

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.

The role involves designing scalable AI solutions, developing ML models, creating recommender systems, and collaborating on data products in a team-focused environment.

The role involves implementing and optimizing low-bandwidth model-parallel training systems for distributed language model development, enhancing an open AI ecosystem.