Senior Machine Learning Engineer (ML Platform)

The role

You will develop and maintain the platform, services, and tooling used to deploy, serve, and operate machine learning models in production. You will contribute to platform architecture and help build a scalable Data Platform for analytics and AI capabilities.

What you will do

• Develop and maintain the platform, services, and tooling used to deploy, serve, and operate machine learning models in production.
• Deploy and operate machine learning workloads across our ML infrastructure.
• Improve automation across the ML lifecycle, including model packaging, deployment, versioning, monitoring, and release processes.
• Maintain and improve the reliability and observability of the ML platform and model-serving services, including logging, metrics, and alerting.
• Participate in the team's on-call rotation, investigate production incidents, and contribute to improvements that prevent them from recurring.
• Collaborate with data scientists, software engineers, and platform teams to turn ML use cases into reliable production solutions.
• Participate in technical discussions and code reviews, contributing to maintainable designs and strong engineering standards.
• Create and maintain clear technical documentation and operational runbooks.

Required qualifications

• 5+ years' experience in ML Engineering, MLOps, or similar roles.
• Proficiency in Python.
• Experience with a managed machine learning platform such as Amazon SageMaker or an equivalent service.
• Practical knowledge of deploying and operating containerized workloads using Docker and Kubernetes.
• Experience developing or operating model-serving platforms, inference services, or backend APIs.
• Familiarity with feature-store concepts, including feature discovery, reuse, versioning, and online/offline consistency.
• Familiarity with model registries, experiment tracking, and ML metadata management.
• Experience with performance, scalability, and reliability considerations for real-time systems.
• Hands-on experience provisioning and managing cloud infrastructure with Terraform.
• Experience with CI/CD pipelines, automated testing, and Git-based development workflows.
• Familiarity with observability practices, including logging, metrics, alerting, and production troubleshooting.
• Strong grasp of software engineering principles and best practices.

About the company

Teya is building a financial platform for local businesses across Europe. The company aims to provide simple tools, thoughtful design, and real human support to entrepreneurs.