Top AI Jobs in Melbourne

Drive consultative B2B SaaS sales for ConvAI by leading discovery calls, demonstrating the Oration platform, building ROI-based business cases, creating tailored proposals and SOWs, and managing the pipeline to close deals using Salesforce.

Partner with business stakeholders to identify AI opportunities, rapidly develop proofs of concept and scalable AI-enabled solutions using approved AI platforms, low-code and automation tools. Drive adoption through workshops, demos, reusable prompts/templates, and coaching while ensuring solutions meet Responsible AI, security, privacy, and governance standards and deliver measurable business value.

Lead end-to-end customer deployments of Cresta's AI SaaS platform across APAC, manage complex, customer-facing projects, define success metrics, ensure smooth launches, drive adoption, and collaborate with product, engineering, and GTM teams to scale AI solutions.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

Freelance AI Evaluators converse with AI chatbots and language models to assess capabilities, safety, and helpfulness. Work includes structured written and voice interactions, submitting ratings, screenshots, recordings or write-ups per task specifications, and completing language and evaluation assessments to inform model development.

As a Senior AI Engineer, you will develop and implement AI capabilities to enhance business processes and customer experiences, collaborating with teams to deliver scalable solutions.

As an AI/ML Engineer, you will develop and optimize AI solutions for renewable energy assets, collaborating with a skilled team to deploy algorithms in real-world projects.

Embed with strategic customers to prototype, build, and productionize full-stack AI and agentic applications. Advise on AI strategy, codify repeatable solution patterns, mentor teams, and feed product improvements.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

Develop and maintain scalable backend services and APIs, collaborate with frontend developers, and lead new features and infrastructure improvements.

Lead technical discovery and hands-on AI workshops to identify, validate, and prioritize private AI use cases. Assess enterprise data readiness, define technical requirements and success criteria, build lightweight proofs of concept and reference architectures, and hand off validated opportunities to engineering teams. Partner with ecosystem providers (e.g., NVIDIA) and regional pods to scale reusable AI patterns across customers and industries.

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.

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 company-wide AI adoption by selecting tools, running workshops, diagnosing team problems, building reusable workflows/automation, tracking tool usage and license ROI, and writing responsible-use guidelines while partnering across Creative, Marketing, Technology, Finance and People teams.

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.

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.