Principal Machine Learning Engineer

Summary

Join Vital as a Principal Machine Learning Engineer and lead our ML efforts, ensuring our AI-powered product features provide the best support to patients. You will work directly with the CTO, setting the technical direction of our ML function while actively writing code. This role involves owning the day-to-day execution of ML engineering initiatives, providing engineering leadership on projects, and acting as the engineering voice in stakeholder conversations. You will work with large datasets (4 million events per day, 750k LLM invocations per week) and contribute to a product impacting millions of patients. As a remote-first company, you can be based in New Zealand or eastern Australia. We move fast, ship to production multiple times a day, and prioritize impact on business outcomes.

Requirements

• Experience in leading and mentoring a team of engineers
• Proven ability to productionize and scale machine learning models
• Strong software engineering skills (e.g., Python, Java, etc.)
• Experience with cloud platforms (e.g., AWS)
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch)
• Experience with CI/CD pipelines
• Excellent communication and collaboration skills

Responsibilities

• Own the day-to-day execution of ML engineering initiatives, focusing on productionising and scaling ML solutions rather than research. So you will organise and run the discipline to ensure smooth delivery of production ready models
• Provide engineering leadership on individual projects while remaining deeply technical; writing code, architecting solutions, and leveraging your software engineering background to build robust ML systems
• Act as the engineering voice in conversations with medical and operations stakeholders, pushing back on hypothetical "couldn't we just..." requests by grounding discussions in technical reality
• Identify opportunities to enhance existing product features through ML improvements and evaluate new models for production readiness, with a focus on platform scalability and maintainability
• Design and implement ML infrastructure including SageMaker pipelines for model retraining, establish architectural patterns, and develop safety frameworks for responsible AI usage including GenAI applications
• Manage ML project timelines and deliverables, communicate progress and technical challenges to executive stakeholders, and serve as the engineering partner to product delivery leads in translating ideas into production reality
• Work flexibly across different team arrangements (without requiring dedicated ML engineering reports), prioritizing impact on business outcomes and product features over traditional hierarchical structures
• Stay connected to ML research developments to inform practical engineering decisions, while maintaining focus on production implementation rather than pure research

Benefits

• Every team member at Vital gets to share in our success in the form of stock options
• We’ll provide you with the equipment you’ll need to work remotely or in a shared office space
• Annual L&D budget to support your career development & a stipend for your home office set up!
• Employee Assistance Program to support your wellbeing
• Paid Parental Leave