ML Ops Engineering Lead

About the Role

Synechron is seeking a highly skilled Machine Learning Platform Engineer to join our technology team supporting a Leading Australian Bank. You will be instrumental in developing deploying and managing end-to-end machine learning workflows in a scalable cloud environment. This role is ideal for professionals who are passionate about ML operations (MLOps) cloud infrastructure and delivering secure and reliable AI/ML solutions at scale.

Key Responsibilities

• Design develop and manage ML workflows using Amazon SageMaker AWS Glue and Apache Airflow.
• Deploy and monitor scalable applications and ML models on Amazon EC2 and AWS Lambda.
• Automate infrastructure provisioning and resource management using AWS CloudFormation.
• Containerize applications using Docker and build robust CI/CD pipelines with GitHub Actions.
• Collaborate with data scientists software engineers and product teams to integrate ML models into production environments seamlessly.
• Write clean efficient and reusable Python code for automation data processing and orchestration.
• Ensure security scalability and reliability of all ML systems and cloud-based deployments in compliance with banking standards.
• Implement monitoring logging and alerting to ensure system health and performance.
• Drive best practices in MLOps including version control testing and reproducibility of ML experiments.

Required Skills and Experience

• 47 years of experience in MLOps Cloud Engineering or Machine Learning Engineering.
• Strong hands-on experience with AWS services particularly SageMaker Glue EC2 Lambda and CloudFormation.
• Proficiency in Python for automation ML workflows and infrastructure scripting.
• Solid experience with Apache Airflow for workflow orchestration and data pipeline management.
• Experience in Dockerizing applications and working with containerized environments.
• Knowledge of CI/CD pipelines using GitHub Actions or similar tools.
• Understanding of machine learning lifecycle model deployment strategies and production monitoring.
• Familiarity with security best practices especially in a regulated industry like financial services.
• Strong collaboration and communication skills with the ability to work effectively across engineering data and business teams.

Preferred Qualifications

• AWS certifications (e.g. AWS Certified Machine Learning Specialty Solutions Architect or DevOps Engineer).
• Experience working in financial services or within large enterprise environments.
• Familiarity with model registry feature stores and experiment tracking tools (e.g. MLflow SageMaker Experiments).
• Exposure to Infrastructure-as-Code tools such as Terraform is a plus.

What We Offer

• Opportunity to work on advanced ML infrastructure and cloud-native solutions with Australias leading bank.
• Access to large-scale real-world ML problems and enterprise-grade tooling.
• Work with a collaborative and innovative team at the forefront of cloud and AI technologies.
• Access to ongoing learning certifications and development resources through Synechrons global programs.

Ready to build the future of AI in banking

• Apply today and be a part of cloud and ML transformation journey with Synechron.

SYNECHRONS DIVERSITY & INCLUSION STATEMENT

Diversity & Inclusion are fundamental to our culture and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity Equity and Inclusion (DEI) initiative Same Difference is committed to fostering an inclusive culture promoting equality diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger successful businesses as a global company. We encourage applicants from across diverse backgrounds race ethnicities religion age marital status gender sexual orientations or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements mentoring internal mobility learning and development programs and more.

All employment decisions at Synechron are based on business needs job requirements and individual qualifications without regard to the applicants gender gender identity sexual orientation race ethnicity disabled or veteran status or any other characteristic protected by law.

Candidate Application Notice