Lead Engineer | Data and Machine Learning Ops

Lead Engineer | Data and Machine Learning Ops

Marley Spoon builds global direct-to-consumer brands leveraging our tech platform and operational excellence to delight our customers in a personalized and sustainable way continuously. We’re global (8 markets, 3 continents), 1600+ employees strong, bringing to market 4 delightful brands: Marley Spoon, Dinnerly, Bezzie and Chefgood. We're a public, solid and 100% carbon-neutral company.

Our 85+ digital team (engineering, product, UX) is structured in 5 tribes. You will be leading an Engineering Team that is responsible for our Data Ops practices. Its mission is to provide teams with the Platform to own and scale all ML use cases end-to-end.

From day one, you’ll have the autonomy to bring your ideas to life, inspire your team of 2 Machine Learning Engineers, and keep learning. Because we know that when you grow, we grow.

Your role is instrumental in shaping our Data Platform to effortlessly support multiple ML models that directly impact business.

Your Role

  • Keep up with the latest trends and have a technology strategy in place, maintained and executed properly
  • Ensure high quality (e.g. performance, maintainability...)
  • Support the team in making good technical and architectural decisions by sharing your knowledge and asking the right questions
  • Collaborate with other teams in creating APIs and SDKs for Real-Time Data Ingestion on the Cloud
  • Provide the Data Science team with the tools to own and scale all Machine Learning use cases end-to-end
  • Build a machine learning platform to increase ML Model development agility and simplify the model serving
  • You have experience in taking technical and architectural decisions and strive to build the best solution rather than the fanciest one
  • Practical experience and solid knowledge of cloud computing concepts
  • Hands-on experience and a broad understanding of modern data technologies - Python, API Development, Machine Learning, Kafka or similar (AWS Kinesis)
  • Containerization (Docker) and Kubernetes
  • Strong interpersonal and communication skills, strong client focus
  • Enjoy sharing knowledge and mentoring other engineers about best practices and our platform
  • Methodical & structured way of working

Awesome extras

  • Experience with event-driven architectures and microservices
  • Good knowledge and experience applying agile methodologies
  • Infrastructure as Code - Terraform
  • AWS Sagemaker (or similar)
  • Autonomy, Impact, Collaboration, Learning & Growth
  • Being part of a profitable company in full-blown scale-up phase - offering immense opportunities for personal & career growth
  • Flexible working hours + Remote or Hybrid Work
  • Spend 5% of your working time on personal learning and development
  • Conference / Training budget
  • Food allowance of 7.62 euros per worked day
  • Health insurance to all employees
  • Company training in different areas
  • Company equipment
  • Company Events
  • Extra Annual leave days
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