AI Jobs in Sydney

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The AI / ML Solutions Engineer at Anyscale is responsible for designing, implementing, and scaling machine learning and AI workloads using Ray and Anyscale directly with customers. This includes implementing production AI / ML workloads such as distributed model training, scalable inference and serving, and data preprocessing and feature pipelines. The role involves working hands-on with customer codebases to refactor or adapt existing workloads to Ray. The engineer advises customers on ML system architecture including application design for distributed execution, resource management and scaling strategies, and reliability, fault tolerance, and performance tuning. They guide customers through architectural and operational changes needed to adopt Ray and Anyscale effectively. Additionally, the engineer partners with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows, supports CI/CD, monitoring, retraining, and operational best practices, and helps customers transition from experimentation to production-grade ML systems. They also enable customer teams through working sessions, design reviews, training delivery, and hands-on guidance, contribute feedback to product, engineering, and education teams, and help develop reference architectures, examples, and best practices based on real customer use cases.

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Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate the core machine learning inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability, then design and implement solutions addressing the highest priority issues.

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Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to their customers for diverse use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models. Build tools to gain visibility into bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.

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Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models. Build tools to provide visibility into bottlenecks and sources of instability, and design and implement solutions to address the highest priority issues.

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Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of deployed models. Build tools to provide visibility into bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues.

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Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core machine learning inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models. Build tools to provide visibility into bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.

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Design, build, and operate scalable back-end systems that power AI agent and workflow builders. Own mission-critical services and infrastructure, delivering impactful features from ideation through to production. Push the boundaries of applied AI by enabling new agent capabilities, workflow orchestration, and system behaviours. Shape how we build by influencing engineering standards, architecture, and processes as we scale. Mentor and support engineers across the team, raising the bar for technical quality and ownership. Set and uphold high standards for code quality, performance, reliability, and security. Collaborate closely with product, design, and leadership to align technical direction with business outcomes.

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Design, build, and operate scalable back-end systems that power real-time, AI-driven chat experiences. Own mission-critical services and infrastructure, delivering impactful features from ideation through to production. Push the boundaries of applied AI by enabling new agent capabilities, workflows, and system behaviours. Shape how the engineering team builds by influencing engineering standards, architecture, and processes as the team scales. Mentor and support engineers across the team, raising the bar for technical quality and ownership. Set and uphold high standards for code quality, performance, reliability, and security. Collaborate closely with product, design, and leadership to align technical direction with business outcomes.

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Design, build, and operate scalable back-end systems that power real-time, AI-driven chat experiences. Own mission-critical services and infrastructure, delivering impactful features from ideation through to production. Push the boundaries of applied AI by enabling new agent capabilities, workflows, and system behaviours. Shape how engineering standards, architecture, and processes are built and scaled. Mentor and support engineers across the team, raising the bar for technical quality and ownership. Set and uphold high standards for code quality, performance, reliability, and security. Collaborate closely with product, design, and leadership to align technical direction with business outcomes.

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Design, build, and operate scalable back-end systems that power AI agent and workflow builders. Own mission-critical services and infrastructure, delivering impactful features from ideation through to production. Push the boundaries of applied AI by enabling new agent capabilities, workflow orchestration, and system behaviours. Shape engineering standards, architecture, and processes as the team scales. Mentor and support engineers across the team, raising the bar for technical quality and ownership. Set and uphold high standards for code quality, performance, reliability, and security. Collaborate closely with product, design, and leadership to align technical direction with business outcomes.