Machine Learning Engineer*
Core
Design, implement, test, deploy, and maintain data- and model-centric systems delivering production-grade ML functionality for sensor-based sorting technologies.
Role type
Machine Learning Engineer (MLOps & Computer Vision)
Builds
End-to-end ML training pipelines, optimized inference models for cloud and edge/sorters, secure data platforms, and internal ML tooling.
Domain
Recycling and waste management industry; Computer Vision and Edge AI
Deliverable
production ML models
Required skills
Python, Computer Vision, MLOps (data modelling, packaging, containerization, CI/CD), Data Science for vision-based model optimization, Cloud and on-prem platform interfaces, Model optimization frameworks (TensorRT, ONNX, CUDA, cuDNN), Edge deployment on hardware (x64, ARM/Jetson)
Preferred skills
TypeScript, REST API development, Modern frontend frameworks (Vue.js, React)
Responsibilities
Build end-to-end ML training pipelines; Deploy, optimize and package models for inference; Support platform team to serve models in cloud; Support ai runtime team to serve models on edge/sorters; Build, integrate and maintain secure data platforms; Design and implement REST APIs to expose ML services; Develop and maintain internal tools and web-based UIs; Apply software engineering practices for version control, code reviews, and accurate technical documentation; Containerize components and implement CI/CD pipelines; Maintain and troubleshoot ML tooling in production.
Seniority
Mid-Senior, hands-on IC
