Senior Machine Learning Engineer

Company Description

About Montu

Montu is one of Australia’s leading health tech businesses and a leader in alternative health services. With operations in Australia and Europe, we take a technology-first approach to reshaping the landscape for suppliers, practitioners, pharmacies and patients.

Montu operates a fully integrated, end-to-end ecosystem of healthcare companies that touches every part of the alternative health experience, from patient care through to pharmacy dispensing, clinical education, product development, wholesale distribution and more. Our brands include Alternaleaf, UMeds, Leafio and Saged.

Recognised by the Deloitte Fast 50 as the fastest growing tech company in Australia for two years running – with revenue growth of over 26,000% and 9,000% – Montu is now the largest business of its kind outside North America.

This role is an Australia-based, fully work-from-home position, with access to co-working spaces in Sydney, Melbourne and Brisbane.

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. This role takes ownership of developing systems that serve our product teams, including
those in customer service, by providing seamless access to advanced Large Language Models (LLMs).

Requiring deep expertise in software development, machine learning, and distributed systems, this role solves for complex needs related to infrastructure and architecture.

Acting as a technical leader and mentor, this role will guide and
collaborate with other engineers, contributing to project execution and launch. 

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:

• Gaining access to SAGED courses and more through the Greenhouse learning platform, fostering continuous growth and development.
• Enjoying 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.
• Enhancing your home office with our ergonomic equipment reimbursement benefit.
• Being part of one of the fastest-growing industries in Australia, improving the lives of hundreds of thousands of patients.

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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.