Machine Learning Architect - Not an Active Opening, Building Talent Pipeline

Caylent

61d•Remote

About The Position

Caylent is a cloud native services company that helps organizations bring the best out of their people and technology using Amazon Web Services (AWS). We provide a full-range of AWS services including workload migrations and modernization, cloud native application development, DevOps, data engineering, security and compliance, and everything in between. At Caylent, our people always come first. We are a global company and operate fully remote with employees in Canada, the United States, and Latin America. We celebrate the culture of each of our team members and foster a community of technological curiosity. Come talk to us to learn more about what it means to be a Caylien! Note: This isn’t an active role right now, but we’re building a community of great talent for future opportunities at Caylent. If your background aligns with what we’re looking for, our team may reach out to learn more about you and explore potential future fits. 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.

Requirements

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.
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).

Responsibilities

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.