Machine Learning Engineer (m/f/d)

Machine Learning Engineer (m/f/d)

Data & AI Lab

Machine Learning Engineer (m/f/d) Data Platform & Enablement Team

Machine Learning Engineer (m/f/d) located anywhere in Europe

Model-to-Production

• You design, develop, and ship ML-powered services as containerized microservices (FastAPI Docker / AWS ECS / Lambda).
• You build robust training, evaluation, and inference pipelines using Python and the PyData stack (e.g., NumPy, Pandas, Scikit-learn).

MLOps & Platform Engineering

• You implement CI/CD for ML (GitHub Actions, Terraform-managed AWS infrastructure).
• You instrument models with observability & experiment-tracking (e.g. W&B, Prometheus, TensorBoard).

Full-stack Enablement

• You prototype customer-facing features or internal tools with React/TypeScript, Streamlit, and/or Gradio.
• You expose models via well-documented RESTful APIs and integrate them into Shopware's product landscape.

Collaboration & Innovation

• You partner with data scientists to move notebooks to production-grade code.
• You explore emerging techniques such as LLMs, RAG systems, and agentic frameworks and assess their fit for Shopware.

Requirements

• Software engineering background: You have 3 years of experience in building and operating production systems in Python, TypeScript, and/or React; familiarity with type safety, testing, and clean-code principles.
• Cloud & IaC: You gained experience on AWS and with Terraform (or similar) to manage infrastructure.
• Machine-learning know-how: You have a solid grasp of supervised/unsupervised learning and deep-learning concepts (CNN, RNN, transformers).
• MLOps mindset: You can work hands-on with CI/CD, Docker, and monitoring/alerting; you are ready to learn advanced MLOps practices if they have not yet been mastered and as needed.
• Full-stack skills: You bring the ability (and willingness) to deliver front-end or integration code in React/TypeScript or similar.
• Nice to have: PySpark/Spark or streaming (Kafka/Kinesis), LLM tooling (LangChain, Hugging Face), vector databases.
• Communication: Very good command of English and enjoyment of remote, cross-functional collaboration.

Benefits

• Company Culture: Open culture with flat hierarchies, where individual initiative is encouraged.
• Employment Contracts: Permanent positions that offer long-term security.
• Flexibility: Flexible working hours and options for mobile work and full-remote contracts.
• Equipment: Freedom to choose your preferred work hardware.
• Onboarding: Well-structured onboarding with support from a personal "buddy."
• Work Environment: An inspiring environment with dedicated colleagues and a dynamic community.
• Development Opportunities: Diverse opportunities for personal growth and development.
• Additional Benefits: Attractive perks such as company pension plans, health programs, and regular team events.
• Team Events
• and much more!

Your personal contact for this position is Carmen Bouraine and is happy to answer any questions you may have! Remote Model: Remote