Senior Machine Learning Engineer / Permanent / Sydney / up to $200,000 + super + bonusAbout the CompanyOur client is a growing data and analytics driven SaaS platform with an established customer base and a proven product.
They're focused on building a sustainable, long‐term business and offer hybrid working in Sydney.About the RoleThis is a software engineering role applied to machine learning.
You'll design, build and automate the infrastructure and tooling behind data science and product workflows, delivering reliable ML pipelines into production.
You'll work closely with experienced data scientists and engineers, with genuine ownership of solutions from design through to delivery.BenefitsSalary range of $150,000 to $200,000+ super (depending on experience)Autonomy to lead initiatives and help shape ML engineering practicesA collaborative team with a strong feedback cultureSenior Machine Learning Engineer / Permanent / Sydney / up to $200,000 + super + bonusAbout the CompanyOur client is a growing data and analytics driven SaaS platform with an established customer base and a proven product.
They're focused on building a sustainable, long‐term business and offer hybrid working in Sydney.About the RoleThis is a software engineering role applied to machine learning.
You'll design, build and automate the infrastructure and tooling behind data science and product workflows, delivering reliable ML pipelines into production.
You'll work closely with experienced data scientists and engineers, with genuine ownership of solutions from design through to delivery.BenefitsSalary range of $150,000 to $200,000+ super (depending on experience)Bonus schemeAutonomy to lead initiatives and help shape ML engineering practicesA team-oriented team with a strong feedback cultureDuties / Key ResponsibilitiesDevelop and refine predictive and forecasting models that feed directly into customer decision‐makingBuild and scale optimisation frameworks to solve complex, constraint‐based problemsDesign and maintain scalable backend services,



APIs and data layers in PythonArchitect event‐driven cloud infrastructure using infrastructure‐as‐code and automated orchestrationTake POCs through to production with clean, well‐tested code and strong CI/CD practicesSkills and ExperienceProven experience building production systems and taking POCs into productionStrong Python skills, with hands‐on experience using common ML and data librariesSolid understanding of the end‐to‐end ML lifecycleExperience building APIs, CI/CD pipelines, testing and deployment automationPublic cloud experience and familiarity with IaC tools such as TerraformWorking knowledge of Docker and KubernetesA product mindset, with a focus on business goals and customer value, not just codeA curious, pragmatic approach: you fix root causes, document issues and are comfortable saying when you don't know somethingEducationBachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, Applied AI, or a related field (or equivalent practical mastery).
Experience4+ years of related industry experience in machine learning, including hands‐on experience designing, evaluating, and operating LLM‐based or agentic systemsStrong coding skills in Kotlin and/or Python, with the ability to write performant, production‐quality code and work effectively with AI‐assisted software development practicesExperience building and operating machine learning systems in production, including the operational practices required to improve system quality, reliability, and costExperience building datasets, evaluations, and benchmarks for systems operating at scale; familiarity with SQL, distributed data processing, and cloud data environmentsA strong ownership mindset and a track record of driving ambiguous technical outcomes from problem definition through delivery and operationStrong communication and influencing skills,



with the ability to explain ML concepts to diverse audiences and steer technical direction with cross‐functional stakeholdersExperience leading technical work and coaching engineers in a collaborative team or virtual squadA pragmatic, iterative approach that balances a high bar for quality with the value of delivering, learning, and improvingIt's great, but not required, if you haveExperience fine‐tuning smaller language modelsExperience serving and operating LLMs using technologies such as NVIDIA Triton Inference ServerExperience applying machine learning to personalisation or context‐aware product experiencesExperience solving complex problems in enterprise SaaS or similarly large‐scale product environmentsBenefits & PerksAtlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community.
Our offerings include health and wellbeing resources, paid volunteer days, and so much more.
To learn more, visit go.atlassian.com/perksandbenefits.About AtlassianAt Atlassian, we're motivated by a common goal: to unleash the potential of every team.
Our software products help teams all over the planet and our solutions are designed for all types of work.
Team collaboration through our tools makes what may be impossible alone, possible together.We believe that the unique contributions of all Atlassians create our success.
To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status.
All your information will be kept confidential according to EEO guidelines.To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process.
Simply inform our Recruitment team during your conversation with them.To learn more about our culture and hiring process, visit go.atlassian.com/crh.In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.
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