Head of Brand Operations for Pepe Chicken, focused on growth and brand management in the digital - first QSR space. Requires extensive brand management experience and fluency in English and French.
About the role
- Senior LLMOps Engineer developing and managing LLMOps infrastructure for AI Care Partner at Heidi. Collaborating with engineers and researchers to optimize model deployment and automation.
Responsibilities
- 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.
- 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.
- Engineer highly available and scalable model serving solutions using modern infrastructure like Kubernetes, ensuring low latency and high throughput for our production services.
- Collaborate closely with AI research and engineering teams to understand their needs, streamline workflows, and create the tooling that accelerates their development cycles.
- Champion and implement best practices for model versioning, experiment tracking, monitoring, and governance across the organization.
- Mentor mid-level and junior engineers, sharing your deep expertise in infrastructure, automation, and operational excellence to foster a culture of reliability and scalability.
Requirements
- 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.
Benefits
- Flexible hybrid working environment, with 3 days in the office.
- 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!
Job title
Job type
Experience level
Salary
Not specified
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Tech skills
Location requirements
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