Myob-2
Senior AI Engineer
Sydney, Australiafull timeunspecifiedtechnology
Machine Learning — Large Language Models (LLMs) — AWS SageMaker — PyTorch — TensorFlow — MLOps — Docker — Kubernetes — AWS Bedrock — Python
Description
Be at the Forefront of AI Innovation at MYOB Are you a forward-thinking Machine Learning Engineer prepared to develop powerful AI solutions that redefine how businesses operate? At MYOB, we empower small businesses with transformative technology. Be part of our Data & AI Team to develop and broaden applications with MYOB’s product ecosystem and data to compose AI-powered experiences for SMEs and Enterprises, enhancing efficiency and confidence. The Role As a foundational member of the AI team, you’ll shape the technical vision and build systems that directly impact our customers' success. This is a unique opportunity to: - Design and implement machine learning systems from the ground up, with a focus on large language models (LLMs) and foundation models tailored to small business needs. - Develop and deploy AI-powered features for automated document understanding, financial forecasting, and conversational interfaces. - Optimise AI systems for scalability, safety, and reliability on AWS infrastructure. - Work in a dynamic, zero-to-one environment, bringing ideas from concept to production. What You’ll Do - Build from Scratch: Develop and optimise machine learning systems, focusing on innovative solutions for small business accounting challenges. - Deploy at Scale: Create scalable workflows to train, deploy, and monitor machine learning models on AWS services like SageMaker and Bedrock. - End-to-End Ownership: Lead projects from ideation to production, implementing MLOps guidelines for robust and efficient solutions. - Collaborate and Innovate: Work with product managers, engineers, and collaborators to align technical solutions with customer and business goals. What You’ll Bring - Technical Expertise: Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and experience with LLMs and foundation models (e.g., GPT, Claude, Llama). - Cloud-Native Experience: Solid understanding of AWS services (SageMaker, Bedrock, S3) and cloud-based architectures. - MLOps Skills: Expertise in CI/CD pipelines for ML, model versioning, monitoring, and containerisation (Docker, Kubernetes). - Customer Focus: Passion for solving real-world challenges for small businesses through innovative AI applications. - Innovation: Excels in uncertain settings, showcasing ingenuity and perseverance to construct influential systems from scratch. - Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field. - Relevant certifications (e.g., AWS Certified Machine Learning – Specialty) are highly desirable.