Top Machine Learning Jobs in Sydney

As a Senior Software Engineer, you will design and implement features focused on digital twins, API development, and engineering simulations. You'll enhance algorithms, improve monitoring, and create tools for efficient data extraction and network design viability assessments.

Lead design, implementation, and productionization of large-scale recommender systems. Integrate research into models, run online/offline experiments, improve ML architecture and serving, collaborate with cross-functional teams, and mentor engineers.

As a Senior Solutions Engineer, you'll provide pre-sales technical support, deliver product demonstrations, and foster customer relationships for Tempo's SPM solutions across the APAC region, focusing on value-based SaaS sales and AI-driven capabilities.

Support Emiri client deployments by bridging product support, UX, and development: investigate issues, triage root causes, configure and QA client models, coach commercial teams, test fixes, and communicate feedback to product. Use Jira/Confluence and apply NLP/ML knowledge to improve processes and user education.

This role involves leading the development of AI systems to replace lab toxicity experiments, focusing on end-to-end ML architecture, research on chemistry-biology correlations, and building innovative models. Candidates should have strong ML skills, engineering abilities in Pytorch and Python, and a passion for both science and technology.

The role involves analyzing biological mass spectrometry data, developing software tools, and scaling workflows for AI and human consumption in drug safety assessment.

The Senior Data Scientist will enhance survey operations, analyze data quality, run experiments, and collaborate with cross-functional teams to solve business problems using advanced data science techniques.

As a Data Scientist at Tracksuit, you will scale survey operations, apply statistical techniques, build data quality systems, and collaborate with product teams to develop brand measurement solutions.

The role involves conducting research in machine vision for deep visual understanding and multimodal learning, developing deep learning methods, and publishing research findings.

Lead Sales Finance for APJ as strategic partner to Sales leadership: own P&L, forecasting, budgeting, variance analysis, KPI tracking, deal desk support, financial modeling, and cross-regional finance projects to drive sales performance and operational improvements.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

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

The Senior Account Executive will develop sales strategies, cultivate relationships with clients, and manage the sales process to close deals with banks and fintechs.

As a Strategic Sales Director, you will lead sales efforts, develop relationships with key executives, and drive significant transactions in Australia.

Serve as Snowflake technical expert for AI/ML workloads: design and build ML/GenAI pipelines, create hands-on POCs using SQL/Python/APIs, enable customers and SIs, resolve technical challenges, and collaborate with product and engineering. Travel to customers ~25%.

Lead design and operation of Neara's ML platform: roadmap for training pipelines, distributed compute, model serving, experiment management, and monitoring. Build tooling to accelerate research-to-production, optimise performance (including custom CUDA/sparse tensors), and enable scalable, secure deployments across cloud and on‑prem environments while mentoring ML engineers.

Bridge research and production by hardening experimental models, optimizing PyTorch training and inference across GPUs, building shared libraries and inference services, improving distributed training and storage workflows, establishing CI/CD and rollout frameworks, and adding observability and reliability to ML systems so research can ship safely and at scale.

Design, implement, and harden production LLM agent execution: planning loop, tool dispatch, memory, retrieval, connectors, retries/timeouts, and security. Improve retrieval latency/cost, instrument executions for training data, and collaborate with Product Security and ML teams to ship reliable systems at scale.

Design and build advanced agentic AI systems: memory/cognitive architectures, multi-agent coordination, autonomous self-improvement loops, safety guardrails, governance patterns, and continuous multi-turn evaluation frameworks to enable reliable, enterprise-grade task agents.

Architect and build a multi-tenant, durable agent runtime and high-throughput memory systems. Own distributed state management, fault-tolerant long-running workflows, strict tenant isolation, MCP-based integration fabric, and platform observability/FinOps to scale agentic AI in production.

As a Machine Learning Engineer, develop ML models for computer vision, integrate with products, manage data and experiments, and work on end-to-end ML operations.

Design, develop and optimise foundation-model and self-supervised learning solutions for healthcare. Build and validate ML training pipelines, evaluate generative models, collaborate with engineering/devops teams, document progress, and apply software engineering best practices for production-ready AI-as-a-medical-device products.

Design, build, and ship production ML systems for content and template generation. Own full ML lifecycle including data pipelines, training, deployment, monitoring, experimentation, and cross-functional collaboration to scale element and template generation.

Ship applied research to improve conversational voice AI: fine-tune and evaluate LLMs for real-time phone workflows, build evaluation frameworks, analyze production conversations, curate and generate training data, investigate regressions, and collaborate with engineering to deploy robust, low-latency models.

The Senior Machine Learning Engineer will design, train, and deploy ML models for optimizing revenue in advertising, taking ownership of product development and leading the ML discipline.