Constructor’s mission is to enable all educational organisations to provide high-quality digital education to 10x people with 10x efficiency.
With strong expertise in machine intelligence and data science, Constructor’s all-in-one platform for education and research addresses today’s pressing educational challenges: access inequality, tech clutter, and low engagement of students.
Please send your resume in English only.Builds and maintains the infrastructure and tooling that keeps machine learning systems reliable in production — from designing CI/CD pipelines and model deployment workflows to monitoring performance and managing model lifecycle at scale. The role works closely with ML, backend, and platform teams, contributes to automation frameworks and observability standards, and helps ensure AI models move seamlessly from experimentation to production. Requires 5+ years of MLOps or DevOps engineering experience, with a track record of operating robust ML infrastructure in production-grade environments.
Mission:Make the path from model experiment to reliable production as fast, automated, and observable as possible.
Education:- Bachelor’s degree or higher in Computer Science, Engineering, or a related field — or equivalent practical experience.
- Design and maintain CI/CD pipelines for ML models and services.
- Build and operate model deployment, serving, and rollback workflows.
- Implement monitoring, observability, and alerting for models in production.
- Manage the model lifecycle with MLflow: experiment tracking, versioning, registries, and reproducibility.
- Automate infrastructure and partner with ML and platform teams on standards.
- 5+ years of MLOps or DevOps engineering experience.
- Strong with containers and orchestration (Docker, Kubernetes).
- Experience with CI/CD (GitLab CI) and infrastructure-as-code (Terraform or similar).
- Hands-on with a major cloud platform (Azure, AWS, or GCP).
- Hands-on experience with MLflow for experiment tracking and model registry.
- Familiarity with ML frameworks (PyTorch), workflow orchestration (Kubeflow or similar), and monitoring stacks.
- Experience serving LLMs or large models in production.
- Knowledge of feature stores and data pipeline tooling.
- Cost and latency optimisation for model serving.
- 💻 Choice of work equipment (e.g., laptop, monitor, etc.)
- 🇬🇧 English classes (iTalki – $130 monthly)
- ⏰ Flexible schedule (we usually work between 09:00/10:00 and 18:00/19:00 CET or EET)
- 👶 Newborn bonus (€500 per child)
- 🧠 Patent remuneration
- 🌴 Paid leave
- 🧑💻 Remote work in locations without our offices
- Hybrid work in locations with offices (2 days in-office, 3 days remote)
Constructor fosters equal opportunity for people of all backgrounds and identities. We are led by a gender-balanced board committed to building a diverse and inclusive organisation where everyone can become their best self. We do not discriminate based on age, disability, gender identity, sexual orientation, ethnicity, race, religion or belief, parental and family status, or other protected characteristics. We welcome applications from women, men and non-binary candidates of all ethnicities and socio-economic backgrounds. We encourage people belonging to underrepresented groups to apply.
Skills Required
- 5+ years of MLOps or DevOps engineering experience
- Bachelor's degree in Computer Science, Engineering, or related field or equivalent experience
- Experience with containers and orchestration (Docker, Kubernetes)
- Experience with CI/CD (GitLab CI) and infrastructure-as-code (Terraform or similar)
- Hands-on experience with a major cloud platform (Azure, AWS, or GCP)
- Hands-on experience with MLflow for experiment tracking and model registry
- Familiarity with ML frameworks (PyTorch), workflow orchestration (Kubeflow or similar), and monitoring stacks
- Experience serving LLMs or large models in production
- Knowledge of feature stores and data pipeline tooling
- Experience with cost and latency optimisation for model serving
What We Do
Constructor group is a global institution dedicated to creating knowledge through science, education, and technology. Our integrated, self-sustainable ecosystem focuses on the five fundamental technology needs expected to contribute to solving the current challenges of the world: general intelligence, quantum technology, intelligent materials, hybrid reality, and life engineering.Our knowledge ecosystem combines extensive education offers covering the entire learning lifecycle from K-12 to post-graduate programs and courses for executives, highly efficient research capacities, and commercial operations for our technology breakthroughs.The Constructor ecosystem comprises Constructor University, a non-profit, research-oriented private university located in Bremen, Germany, and an institute in Schaffhausen.Several ventures market our technology innovations: Alemira and Learning focus on advanced solutions in Educational Technology, executive education, and consulting services. Rolos delivers a platform boosting research productivity and develops MI for robotics and driverless mobility. Capital and Start Garden further strengthen our ecosystem by offering funding and start-up incubation capacities.
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