Top Machine Learning Jobs in Sydney

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

Serve as the primary escalation for complex technical support issues for an AI/ML product. Manage high-volume, high-impact tickets, lead customer calls, reproduce and track bugs with Engineering/Product, mentor peers, improve documentation and playbooks, and surface patterns to drive product and operational improvements.

Lead strategic Data Science initiatives across corporate areas, manage complex data projects, and enhance decision-making through data-driven insights.

As the Tech Lead Manager, you will lead an engineering team, drive project delivery, manage workflows, and provide technical leadership while maintaining hands-on involvement in system design and architecture.

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

The Key Account Manager role involves driving growth in large utility accounts, ensuring customer value realization, and managing ongoing relationships to uncover new opportunities and solve client challenges.

This role leads enterprise-scale AI and Data transformation programs, acting as a trusted advisor to senior executives, and shaping data strategies and governance frameworks.

As a Solutions Architect at Anthropic, you will advise large enterprises on integrating AI solutions, support technical deployments, and collaborate with teams to guide customer success.

As a Senior Software Engineer, you'll design and implement features related to digital twins, data abstractions, and structural analysis, leveraging machine learning and algorithms.

As a Quantitative Researcher at Akuna, you will develop trading strategies using machine learning, analyze experiments, and build metrics for strategy evaluation.

As Head of Data Product, lead strategy for Consumer Brands, manage data product roadmaps, and drive integration of AI and Machine Learning initiatives.

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

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.

The role involves building and maintaining production-grade ML systems, transitioning models from research to production, and collaborating with data scientists to ensure compliance and scalability.

The role is responsible for managing AI infrastructure, building scalable systems for AI features, and collaborating with teams to enhance AI capabilities.

The Customer Success Engineer will act as a technical resource for enterprise customers, driving platform adoption and delivering quantifiable ROI through effective client engagement and support.

As a Customer Value Architect, you'll enhance customer engagement by translating software capabilities into measurable outcomes while fostering strong client relationships and driving product adoption.

Design and implement robust, large-scale distributed ML training systems optimized for low-bandwidth, high-latency environments. Build model-parallel training strategies, checkpointing and recovery, GPU and memory optimizations, P2P networking, NAT traversal, and monitoring to ensure resilient, efficient multi-participant training.

The Principal Software Engineer will design and prototype AI/ML solutions, provide architectural guidance, and mentor engineering teams to apply innovative technologies across the Objective suite.

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.

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.

The Data Engineer will support the Data Analytics team by delivering quality datasets, managing data architecture, and optimizing data pipelines using tools like Python, SQL, and AWS.

The Senior Machine Learning Engineer will own the end-to-end ML lifecycle, design and deploy models, and directly engage with customers to develop AI/ML solutions, focusing on enhancing developer experiences.

The role involves designing, building, and scaling ML/RL systems that enhance customer experience while ensuring reliability and efficiency in production. Responsibilities include model optimization, deployment, and monitoring for performance improvements.