Top Tech Jobs & Startup Jobs in Melbourne

Drive growth across non-car marketplace verticals by prospecting, converting, and onboarding new dealers. Identify business opportunities, support client acquisition and retention, use market and customer data to uncover opportunities, monitor competitors, cross-sell value-added products, and collaborate across teams to meet financial goals. The role requires strong sales or business development experience, achievement of KPIs and targets, and excellent relationship-building and presentation skills.

Manage a national portfolio of automotive dealer clients as the primary contact. Maintain program compliance and service agreements, strengthen partner relationships, monitor performance standards, collaborate through meetings and reporting, resolve issues, and improve operational processes. The role requires account management, sales or performance management experience, KPI achievement, strong communication and presentation skills, data interpretation, and proficiency with Excel and PowerPoint.

Provides cross-team architectural direction for the data platform, shapes technical strategy, establishes engineering standards, oversees major modernization initiatives, mentors engineers, evaluates emerging tools, and resolves complex cross-domain technical challenges. Requires deep expertise across Snowflake, dbt Cloud, Python, RabbitMQ, PostgreSQL, and AWS, plus strong stakeholder communication and architectural leadership.

Own and evolve major areas of the data platform, ensuring reliability, quality, scalability, and cost efficiency. Lead Snowflake performance optimization, dbt modeling standards, pipeline architecture, observability, incident resolution, and governance. Partner with product, commercial, and analytics stakeholders to translate requirements into solutions. Mentor engineers, improve team capability, and evaluate responsible AI tooling for data engineering workflows.

Lead end-to-end data science initiatives involving exploratory analysis, behavioral insights, experimentation, recommendation, ranking, personalization, and machine learning. Develop and productionize models, design offline and online evaluations, measure commercial impact, and establish rigorous modeling and documentation standards. Collaborate with Product, Data, Technology, and Commercial teams to solve complex customer problems and improve vehicle marketplace experiences.

Own the design, deployment, and operation of machine learning systems on AWS. Provide technical leadership to data science and ML engineering teams, productionize experiments, standardize model delivery, build monitoring feedback loops, optimize cloud costs, remediate security risks, and improve engineering practices through guidance and collaboration.

Senior Product Designer responsible for defining and delivering user-centered product experiences across the buyer and seller journey. The role involves presenting design concepts, identifying user problems and product pain points, creating intuitive and accessible interfaces, and collaborating with product strategists, technical leads, developers, and cross-functional teams to manage scope, timelines, and quality.

Own the AI product’s vision, strategy, performance, growth, and commercial outcomes. Lead customer and market insight analysis, experimentation, prioritization, opportunity discovery, product delivery, optimization, and cross-functional alignment. Build and scale AI and personalization experiences for millions of users while influencing senior stakeholders, managing dependencies, and partnering with vendors and external teams.

Manage the end-to-end delivery of digital advertising campaigns for automotive dealer clients, including onboarding, setup, QA, launch, monitoring, optimization, bid management, keyword strategy, audience refinement, creative testing, and troubleshooting. The role combines Google and Meta advertising expertise with consultative B2B sales to improve campaign performance, generate qualified leads, and grow advertising revenue.

Leads engineering execution for Machines4U, including product development, platform reliability, delivery cadence, technical roadmaps, modernization, integrations, security, and compliance. Manages a distributed engineering team, partners with product and group engineering stakeholders, guides architecture and technical trade-offs, and communicates engineering risks, capacity, and priorities to senior leadership.