Senior Machine Learning Engineer
vor 4 Wochen
Job Title: Senior Machine Learning Engineer
Company: Montu
Location: Australia-based, fully work-from-home position, with access to co-working spaces in Sydney, Melbourne, and Brisbane.
Montu is one of Australia's leading health tech businesses and a leader in alternative health services.
We take a technology-first approach to reshaping the landscape for suppliers, practitioners, pharmacies, and patients.
Recognised by the Deloitte Fast 50 as the fastest growing tech company in Australia for two years running, Montu is now the largest business of its kind outside North America.
Job Description: The Senior Machine Learning Engineer is a leading contributor in developing and enhancing the core infrastructure for our team of software engineers, machine learning engineers, and data scientists.
This role involves the design, architecture, and implementation of cutting-edge machine learning models and pipelines, with a focus on scalability, robustness, and efficiency.
Day to day: Design, implement, and maintain machine learning pipelines for model training, validation, and deployment.Automate end-to-end model lifecycle management, including data preprocessing, model training, testing, monitoring, and updates.Collaborate with data engineering teams to build scalable, resilient, and secure infrastructure for ML models in production.Ensure CI/CD practices for model deployment, including version control, testing, and rollback strategies.Monitor model performance, identify bottlenecks, and implement improvements to maintain optimal results.Develop tools and frameworks for the rapid deployment and iteration of machine learning models.Optimise resource usage and cost by ensuring efficient model inference and serving architectures.Maintain and improve data pipelines, ensuring data quality, availability, and integrity.Collaborate with cross-functional teams to understand business needs and translate them into actionable ML solutions.Ensure compliance with data privacy and security standards in model handling and deployment.Qualifications: Proficiency in Python and TensorFlow, PyTorch, or other relevant ML libraries.Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud for ML deployment.Strong understanding of CI/CD pipelines, containerisation (Docker, Kubernetes), and orchestration tools.Experience with monitoring tools like Datadog, Grafana, or similar to track model performance.Knowledge of infrastructure-as-code tools like Terraform or CloudFormation.Experience with version control (Git) and workflow automation.Familiarity with distributed data systems like Spark, Hadoop, or Kubernetes.Strong problem-solving skills and a commitment to continuous learning.Excellent communication skills, both written and verbal.Additional Information: You'll be joining a highly motivated, agile team where your ideas and work will directly influence the direction and progress of an expanding global company in a hyper-growth phase.
We pride ourselves on our collaborative and driven culture and offer opportunities for advancement to high achievers.
Other benefits include: Access to SAGED courses and more through the Greenhouse learning platform.Discounts with over 450 retailers through our Reward and Recognition platform.The freedom of a full-time, work-from-home role.Access to co-working spaces in Sydney, Melbourne, Brisbane, and select regional cities.Mental health support through our wellbeing platform, Unmind.A private health insurance discount through Medibank.Up to 8 weeks of paid parental leave.Swag kits to celebrate key milestones in your journey with us.Ergonomic equipment reimbursement benefit for your home office.Being part of one of the fastest-growing industries in Australia, improving the lives of hundreds of thousands of patients.We are committed to facilitating a barrier-free recruitment process and work environment.
If you require any accommodations, we welcome you to let us know so we can work with you to participate fully in our recruitment experience.
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