Senior LLMOps Engineer

Who are Heidi?

Heidi is on a mission to halve the time it takes to deliver world-class care.

We believe that by 2050, every clinician will practice with AI systems that free them from administrative burdens and increase the quality and accessibility of care to patients across the world.

Built for clinicians, by clinicians, at the core of Heidi is its people. We are an eclectic bunch of inventors, builders, scientists, nurses, doctors, mathematicians, designers, creatives, and high-agency executors.

We achieve in 6 months what it takes our competitors 4 years to do. In just 12 months, 20 million patient consults were supported by Heidi, and we're now powering more than 1 million consults every week.

With our most recent $16.6MM round of funding from leading VC firms, we're geared up to supercharge our ambitious global growth, starting with the US, Canada, UK and Europe - and we need great people like you to get there.

The Role

Working closely with our Engineering Manager, you'll be a Senior LLMOps Engineer on the Model Platform team. You are a technical leader responsible for building and scaling the infrastructure that powers our entire model lifecycle.

Your mission is to build a robust, scalable, and reliable platform for deploying and managing our LLMs. You will lead the design and implementation of our LLMOps strategy, ensuring our AI engineers can move models from development to production seamlessly and efficiently.

You will combine your deep infrastructure knowledge with MLOps principles to solve the critical challenges of serving models at scale.

What you'll do:

• Lead LLMOps Platform Development: Lead the architecture, design, and implementation of our end-to-end LLMOps platform, from data ingestion and model training pipelines to production deployment and monitoring.
• Automate the LLM Lifecycle: Build and maintain robust CI/CD/CT (Continuous Integration/Continuous Delivery/Continuous Training) pipelines to automate the testing, validation, and deployment of large language models.
• Ensure Scalable and Reliable Deployment: Engineer highly available and scalable model serving solutions using modern infrastructure like Kubernetes, ensuring low latency and high throughput for our production services.
• Partner with AI and Engineering Teams: Collaborate closely with AI research and engineering teams to understand their needs, streamline workflows, and create the tooling that accelerates their development cycles.
• Establish MLOps Best Practices: Champion and implement best practices for model versioning, experiment tracking, monitoring, and governance across the organization.
• Mentor and Guide: Mentor mid-level and junior engineers, sharing your deep expertise in infrastructure, automation, and operational excellence to foster a culture of reliability and scalability.

What we will look for:

• You've a proven track record of designing, building, and maintaining MLOps or LLMOps infrastructure in a production environment.
• You've previous hands-on experience building scalable, cloud-native infrastructure and platforms.
• You've deployed and managed large-scale machine learning models in a production environment, with a deep understanding of the associated challenges.
• You are considered an expert in Python, cloud platforms (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and Infrastructure as Code (e.g., Terraform, CloudFormation).
• You have a deep and practical understanding of the entire machine learning lifecycle and the specific operational challenges of large language models.
• You have the ability to translate complex engineering and research requirements into concrete, robust, and automated platform solutions.
• A Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Bonus:

• Experience with advanced model serving and optimization techniques (e.g., quantization, distillation, multi-model serving).
• Experience with specialized MLOps frameworks like MLflow, Kubeflow, or Weights & Biases.
• Contributions to open-source MLOps or infrastructure-related projects.

What do we believe in?

• We create unconventional solutions to difficult problems and we build them fast. We want you to set impossible goals and make them happen, think landing a rocket but the medical version.

• You'll be surrounded by a world-class team of engineers, medicos and designers to do your best work, inspired by our shared beliefs:

• We will stop at nothing to improve patient care across the world.

• We design user experiences for joy and ship them fast.
• We make decisions in a flat hierarchy that prioritizes the truth over rank.
• We provide the resources for people to succeed and give them the freedom to do it.

Why you will flourish with us ?

• Flexible hybrid working environment, with 3 days in the office.
• Additional paid day off for your birthday and wellness days
• Special corporate rates at Anytime Fitness in Melbourne, Sydney tbc.
• A generous personal development budget of $500 per annum
• Learn from some of the best engineers and creatives, joining a diverse team
• Become an owner, with shares (equity) in the company, if Heidi wins, we all win
• The rare chance to create a global impact as you immerse yourself in one of Australia's leading healthtech startups
• If you have an impact quickly, the opportunity to fast track your startup career

Help us reimagine primary care and change the face of healthcare in Australia and then around the world.