Machine Learning Architect – Talent Pipeline

About the role

Caylent is seeking a Machine Learning Architect to join its Cloud Native Applications team. This position is focused on designing ML systems, guiding customers and internal teams, and delivering AWS‑based solutions for cutting‑edge projects.

Key responsibilities

• Lead Agile ceremonies, translate customer requirements into actionable backlogs, and delegate tickets to engineering teams.
• Conduct requirements gathering, backlog grooming, and architecture discussions.
• Apply DevOps best practices, including CI/CD, IaC, security, monitoring, and logging.
• Troubleshoot and resolve issues across development, test, and production environments.
• Automate testing at multiple levels and write production‑quality code with unit and integration tests.
• Mentor and coach less‑experienced teammates while learning from senior engineers.

Required profile

• Strong consulting mindset with a focus on customer experience and clear communication.
• Ability to facilitate alignment across stakeholders and navigate differing technical perspectives.
• Proven experience breaking down complex technical concepts for non‑technical audiences.

Required skills

• Infrastructure as Code tools: CloudFormation, CDK, Terraform.
• Amazon SageMaker and ML libraries: TensorFlow, MXNet, PyTorch, Scikit‑learn.
• Deep understanding of ML concepts such as feature engineering, hyperparameter tuning, and optimization.
• MLOps tools: MLflow, Neptune, Comet.

What we offer

• USD‑based compensation and competitive phantom equity.
• 100% remote work with up to 25% travel as needed.
• Generous holidays, flexible PTO, and an equipment stipend.
• Paid exams, certifications, peer bonuses, and a professional development budget.