4 months ago
Melbourne, AustraliaStaff+
Responsibilities
- Design and implement machine learning systems with a focus on LLMs and foundation models.
- Develop AI-powered features for automated document understanding, financial forecasting, and conversational interfaces.
- Build scalable workflows to train, deploy, and monitor machine learning models on AWS.
- Lead projects from ideation through production and apply MLOps practices.
- Optimize AI systems for scalability, safety, and reliability.
- Shape the AI team’s technical vision and mentor, coach, or lead other engineers.
- Collaborate with product managers, engineers, and stakeholders to align solutions with customer and business goals.
Requirements
- Proficiency with machine learning frameworks such as TensorFlow and PyTorch.
- Experience with LLMs and foundation models such as GPT, Claude, and Llama.
- Strong knowledge of AWS services including SageMaker, Bedrock, and S3.
- Expertise in ML CI/CD pipelines, model versioning, monitoring, and containerization with Docker and Kubernetes.
- Experience providing thought leadership and mentoring, coaching, or leading others.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
- Relevant certifications such as AWS Certified Machine Learning – Specialty are highly desirable.
Benefits
- Flexible hybrid workplace with centrally located offices and in-person celebrations and social events.
- Financial assistance for setting up a home office, plus corporate discounts and retail vouchers.
- Wellbeing support through the Sonder partnership.
- In-house training, LinkedIn Learning, conferences, and study assistance.
- Multiple leave options, including purchased leave, parental leave, domestic violence leave, transgender leave, community leave, and study leave.
- Communities focused on Wellness, Belonging, and the Planet.
Tech Stack
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