Overview
In this role you help shape and scale Teya’s ML platform, delivering production-grade ML workloads and data-driven capabilities for local businesses across Europe. You’ll collaborate with data scientists, software engineers, and platform teams to deploy, monitor, and evolve ML services in production, enabling both analytics and AI use cases. The position emphasizes reliability, observability, and a strong engineering culture as the company builds a scalable data platform. You join a fast-paced team that values quality, detail, and real human support for customers. This role offers the chance to influence core ML infrastructure and drive impactful, city-scale solutions.
Responsibilities
- Develop and maintain platform services and tooling to deploy, serve, and operate ML models in production
- Deploy and manage ML workloads across the ML infrastructure
- Improve automation across the ML lifecycle (packaging, deployment, versioning, monitoring, releases)
- Enhance reliability and observability of ML services (logging, metrics, alerts)
- Participate in on-call rotations and investigate production incidents
- Collaborate with data scientists, software engineers, and platform teams to turn ML use cases into reliable production solutions
- Contribute to technical discussions, code reviews, and maintainable designs
- Create and maintain technical documentation and runbooks
Key requirements
- 5+ years in ML Engineering, MLOps, or similar roles
- Proficiency in Python
- Experience with managed ML platform (e.g., Amazon SageMaker)
- Experience deploying containerized workloads with Docker and Kubernetes
- Experience developing or operating model-serving platforms or backend APIs
- Familiarity with feature-store concepts (discovery, versioning, online/offline consistency)
- Familiarity with model registries, experiment tracking, ML metadata management
- Experience with performance, scalability, and reliability for real-time systems
- Hands-on experience provisioning and managing cloud infrastructure with Terraform
- Experience with CI/CD pipelines, automated testing, and Git workflows
- Familiarity with observability practices (logging, metrics, alerting, production troubleshooting)
- Strong software engineering principles and best practices
- Experience contributing to data warehouse architecture or redesign initiatives
- Ability to collaborate with technical and non-technical stakeholders
- collaboration
- communication
- problem-solving
- Python
- Amazon SageMaker or similar managed ML platform
- Docker
Senior Machine Learning Engineer (ML Platform) in London employer: Teya Solutions
At Teya, we believe in empowering local businesses with innovative financial solutions, and as a Mobile Shift Engineer, you'll be at the forefront of this mission. Our flexible working hours, comprehensive health insurance, and a supportive, informal office culture foster both personal and professional growth, making Teya an exceptional place to develop your skills while contributing to meaningful change in the community. Join us to create impactful products that truly make a difference for entrepreneurs across Europe.
