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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Expert (all genders) - **Company:** Nect GmbH - **Location:** Hamburg, Germany (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Computer Vision, Biometrics, Continuous Integration, Distributed Systems, Python (Programming Language), PostgreSQL, Machine Learning, Tensorflow, Azure Machine Learning, Software Engineering, SQL Databases, Cloud Platform System, Pytorch, Flask (Web Framework), Deep Learning, Model Validation, Reliability of Systems, Backend, Gitlab-ci, Information Technology, ONNX (Open Neural Network Exchange) Format, Machine Learning Operations, Restful APIs, Docker, Microservices - **Published:** May 20, 2026 - **Apply:** https://de.indeed.com/viewjob?jk=3eea6292fb20dae0 ## About the Role Do you have a Master's degree?, * Master's degree or PhD in Computer Science, Machine Learning, Software Engineering, or related field. * 5+ years of software engineering experience, including at least 3 years in machine learning engineering. * Strong proficiency in Python and backend development. * Experience building and deploying production-grade ML systems in cloud environments. * Hands-on experience with distributed systems and microservices architectures. * Strong understanding of the machine learning lifecycle and MLOps practices. * Experience deploying models via REST APIs or real-time inference services. * Familiarity with SQL databases. * Strong problem-solving mindset and excellent communication skills. * Fluent English skills required; German is a plus. Tech Stack * Python * Flask, Gunicorn * TensorFlow, PyTorch, ONNX, PaddlePaddle * Docker * PostgreSQL * GitLab CI * REST APIs ## Description In this role, you will collaborate closely with ML scientists, backend engineers, DevOps teams, and product stakeholders to productionize advanced AI models used by millions of users every day., Machine Learning Engineering * Design, develop, deploy, and optimize machine learning systems for identity verification products at scale. * Productionize advanced AI and deep learning models in collaboration with ML scientists and engineering teams. * Improve model performance, reliability, scalability, and inference efficiency. * Build and maintain robust ML pipelines for training, deployment, monitoring, and retraining. * Optimize real-time inference systems for high-throughput production environments. Backend & Infrastructure * Develop scalable Python-based backend services and microservices architectures. * Deploy ML models through REST APIs and real-time inference services. * Work with distributed systems and cloud-native infrastructure. * Contribute to CI/CD workflows and operational excellence for ML services. Collaboration & Technical Contribution * Work cross-functionally with Product, Engineering, Infrastructure, and Security teams. * Participate in architecture discussions and technical decision-making. * Help drive best practices in MLOps, scalability, and system reliability. ## Related Videos - [Data Science, ML & AI in the Oil and Gas Industry at NDT Global - Dr. Katja Träumner](https://www.wearedevelopers.com/videos/1308-data-science-ml-ai-in-the-oil-and-gas-industry-at-ndt-global-dr-katja-traumner) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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