Top AI Jobs in Sydney

Outlier seeks experienced software engineers to assist in training AI models by crafting and answering questions related to computer science and evaluating AI-generated code. This flexible freelance opportunity allows contributors to improve the coding capabilities of generative AI models.

This role involves applying innovative AI and automation solutions in the context of clinical trials to enhance efficiency and efficacy. The engineer will work with a diverse team to initiate transformative changes and deliver impactful results in healthcare.

The Principal Software Engineer will lead the development of advanced search solutions at Walmart, utilizing technologies like Elastic Search and OpenAI. Responsibilities include architectural planning, project leadership, collaboration with cross-functional teams, and guiding junior engineers while ensuring code quality through test-driven practices.

The Full Stack Engineer will develop an AI-powered agency management system, focusing on frontend and backend components, integrating AI models, ensuring system scalability and security, and collaborating with cross-functional teams.

As a Senior AI Engineer, you will work on enhancing Dovetail's AI features, mentor junior engineers, drive AI enablement across teams, and stay updated with the latest technologies to influence product development. You'll collaborate on producing robust Machine Learning systems and maintain high-quality software practices.

The Staff Software Engineer will lead the development and deployment of advanced AI and machine learning models, collaborating with diverse teams to engineer scalable AI solutions that meet business needs. Responsibilities include designing AI architectures, conducting performance evaluations, coaching team members, and influencing stakeholders on modern best practices.

As a Senior Staff Engineer in Generative AI Engineering, you will lead the design and implementation of innovative AI solutions, ensuring adaptability and reliability of software. You will mentor engineers, drive the adoption of best practices, and partner with stakeholders to influence Gen AI strategies in the banking sector.

The Senior Associate Data Scientist will design and implement advanced machine learning models to enhance lending decisions and optimize risk management. The role involves developing cutting-edge AI solutions, collaborating with stakeholders, and utilizing strong analytical skills to drive data-driven innovation across diverse business challenges.

The Chapter Lead will oversee engineering teams developing Generative AI solutions to enhance customer engagement and internal tools for a leading bank. Responsibilities include ensuring solution quality, capability uplift, and team management while fostering innovation in the emerging fields of Prompt Engineering and Knowledge Management.

The AI/ML and MLOps Field Engineer at Canonical will assist global companies in adopting AI using open source technologies on cloud infrastructures, primarily focusing on Linux and Kubernetes. Responsibilities include architecting cloud solutions, engaging in customer interactions, and solving complex data architecture problems using various data technologies.

The AI Engineer / Technical Pre-Sales Engineer will design, develop, and implement state-of-the-art AI solutions, collaborating with clients to understand their needs and align solutions with business outcomes. The role includes technical pre-sales activities and involvement in both project work and innovation in AI technologies.

Outlier is seeking skilled coders to assist in training generative AI models by crafting computer science-related questions and evaluating AI-generated code. This remote freelance role offers flexible hours, with pay rates starting at $30 per hour, varying based on expertise and project needs.

The Software Engineer will be responsible for developing large new areas within data management software, handling the entire product lifecycle, and ensuring high reliability of system software. This role demands experience with AI infrastructure at scale and solid Python knowledge. Multi-tasking and quick adaptation to new technologies are essential.