Machine Learning Architect

We are seeking an exceptional Machine Learning Architect to join our growing Cloud Native Applications team. The right candidate is someone who has deep expertise in ML system design and is passionate about working with our customers, partners, and colleagues to drive innovation forward. Your mission will be to work alongside Caylent’s Engineers, Engineering Managers, and Project Managers to deliver AWS solutions across our diverse and forward-thinking customer base. You’ll work with the latest technologies and support customers looking to bring cutting-edge ideas to market.

• You will be a mission control specialist, guiding Cayliens and Customers alike through Agile ceremonies like stand-ups, retrospectives, and more.
• You will translate customer requirements and into a workable backlog of tickets for engineers.
• Delegate tickets to a team of engineers in order to complete customer projects.
• Lead requirements gathering, backlog grooming, and architecture discussions.
• Apply your understanding of DevOps pipelines, including build automation, branching strategies, CI/CD, Infrastructure as Code, security, monitoring, logging, and alerting.
• Troubleshoot and resolve issues in customer dev, test, and production environments.
• Automate software testing at multiple levels (component, configuration item, subsystem, system) and monitor results.
• Write production quality code, including unit and integration tests. 
• Work with a team to deliver top-quality cloud native applications on AWS for customers.
• Clearly communicate and document your designs, processes, and procedures.
• You will demonstrate a passion to Stay Curious as you mentor peers, tackle new technologies, and learn from our word-class team of engineers.
• Coach and mentor less experienced teammates, coach and be mentored by world class engineers.

Core Consulting Qualifications 

Customer Experience 

• Confidently addresses client questions and identifies gaps in requirements with  proposed next steps. 
• Focus on delivering clear, actionable solutions that meet client goals

Collaboration 

• Facilitates alignment across stakeholders or technical priorities and deliverables.
• Navigates differing perspectives with professionalism to ensure shared understanding  and progress. 

Communication 

• Breaks down complex technical concepts for non-technical audiences in a clear, concise  manner. 
• Adapts communication style based on audience and context to improve clarity and decision-making. 

Technical Qualifications

• Experience with IaC tools (CloudFormation, CDK, Terraform).
• Expert level experience in Amazon SageMaker and ML libraries (TensorFlow, MXNet, PyTorch, Scikit-learn).
• Strong understanding of ML concepts: feature engineering, hyperparameter tuning, optimization strategies.
• Familiarity with MLOps tools (MLflow, Neptune, Comet).