Top AI Jobs in Sydney

Support maintenance and improvement of regulatory compliance content: perform legal research, draft and edit content, update formatting and metadata, conduct quality reviews, manage documentation and workflows, and assist content managers with day-to-day operational tasks across jurisdictions.

Validate and improve AI-generated legal and regulatory compliance outputs through legal research, testing, identifying gaps and edge cases, and providing structured feedback to product, engineering and data science teams. Support prompt design, evaluation frameworks, training data, taxonomy and metadata, and work across Australian, UK and global regulatory environments to enhance AI accuracy and customer outcomes.

Develop and optimize backend architecture for a multi-brain AI trading system. Design and implement AI/ML models and workflows, integrate blockchain and smart contracts, build and maintain APIs, databases, and cloud infrastructure, perform code review, testing, debugging and performance optimization, and ensure security, data integrity, and production readiness.

Build and ship AI-driven GTM systems: outbound lead engine, inbound/lifecycle automations, AI-assisted content pipeline, data/reporting layer, and fast production patches to eliminate manual marketing workflows.

Drive the expansion of software development and AI services by managing client relationships, building sales pipelines, and negotiating contracts.

PhD research integrating computer vision, large and small AI models, formal reasoning, reinforcement learning, and robot control to enable trustworthy humanoid robots for high-risk tasks. Work includes hands-on experiments with robotic platforms, multimodal sensors, simulation, and industry collaboration in explosive ordnance disposal, mining, and construction.

Design, build and maintain automation and AI/LLM integrations to reduce manual work, improve accuracy and security, connect business systems, create dashboards, and enforce governance, documentation and testing so tools are reliable and auditable.

As an AI Consulting Solutions Engineer, you'll lead pre-sales efforts for Netskope's AI Security products, assist sales teams, engage customers, and collaborate with product management.

The AI Platform Engineer leads the development of production AI agents and components, collaborates on AI implementations, and maintains AI systems for reliability and observability.

Lead generative AI image production for realistic personas and models. Build and optimize scalable generative pipelines, automate batch workflows, evaluate new models/tools, define technical direction and best practices, and improve image quality, consistency, speed, and cost-efficiency.

Lead client-facing AI adoption programmes end-to-end: design change strategies, build executive sponsorship and champion networks, measure behaviour change and ROI, run executive workshops and company-wide engagement, codify playbooks, and drive renewal and expansion through sustained adoption.

Define safety, usability, and performance metrics for AI and robotic products; translate VLA and agentic RAG breakthroughs into customer value; engage enterprise adopters for feedback; lead cross-functional teams; own product roadmap and delivery for agentic and robotic deployments.

Develop and train foundation models for robotics, align text-based reasoning with low-level control policies, design and run zero-shot generalization experiments, collaborate with interdisciplinary teams, and present research findings at conferences.

Design and implement multi-agent orchestration frameworks, build tool-calling pipelines and reasoning loops, and optimize latency and token usage for real-time agentic workflows.

Design and implement HRI systems: build intent-recognition models from gaze, gesture, and voice; create socially aware navigation algorithms; and design visual and auditory robot feedback and interfaces. Run user studies and prototype AI-driven voice and visual interfaces to validate interaction paradigms.

Perform adversarial testing and red-teaming on large language and multimodal models, implement runtime guardrails and filtering, and help develop constitutional AI principles and RLHF alignment pipelines to ensure safe AI deployment.

Design, deploy, and maintain MLOps infrastructure: manage model registries, continuous training loops, and A/B testing. Deploy agentic systems as scalable microservices on Kubernetes and build observability dashboards tracking token usage, latency, and agent reasoning.

Design and optimize multimodal AI systems integrating vision and audio models. Improve voice-to-voice streaming latency, embed vision encoders and audio-native models into agent reasoning, and architect multimodal RAG systems for retrieving insights from videos and PDFs.

Optimize and compress large language and vision models for on-device inference. Develop distillation and hardware-specific compilation pipelines, deploy models to edge devices, and benchmark performance across NPU/GPU architectures to ensure efficient on-device operation.

Lead orchestration and optimization of large-scale LLM pretraining across 1,000+ GPUs. Manage distributed training with PyTorch/DeepSpeed/Megatron-LM, tune networking and memory (InfiniBand/RDMA), and implement checkpointing and robust failure recovery for long-running jobs.

Independent full-cycle recruiter managing sourcing, client engagement, offer negotiation, and placements using AI-driven tools. Acts as commercial advisor, provides market insights, and maintains self-directed billing and activity in a results-only, remote environment.

Own end-to-end Instagram Reels production: ideation, scripting, editing, and delivery. Use AI tools to support ideation and production, test formats, optimize for retention, and stay on top of short-form video trends to grow international audiences.

The AI Video Editor / Motion Designer creates AI-driven videos to enhance advertising effectiveness. Responsibilities include video production, concept development, utilizing AI tools, performance analysis, and collaboration with team members.

Design and ship a 14-domain skills taxonomy and SDK/CLI tooling, operate the MCP server, integrate agent protocols, improve LLM grounding for crypto, run developer hackathons, and produce technical content to grow the ecosystem.

Lead and improve Microsoft 365, Power Platform, Dynamics 365 and AI capabilities. Manage governance, security, vendor relationships and platform adoption while partnering with stakeholders to deliver productivity, automation and business-aligned solutions.