Today technology is driving the world. And at METRO digital we are driving the technology for one of the leading international wholesalers specializing in food - METRO. From ecommerce to checkout, to delivery software, we work on a wide range of products to meet the needs of our users - METRO’s customers and employees from across 25 countries. With passion and responsibility, we move the wholesale industry towards digitization and leverage METRO’s long history and expertise in B2B for building a more sustainable market ecosystem.
What you can expect:
- Holistic approach: You are involved in all phases of data and ml-engineering, from data preparation over model implementation to testing and ultimately running it on the cloud. A high working quality, which is ensured by extensive test automation.
- Teamwork: You are part of independent data science team with colleagues from all over the world which develop predictive and recommender system models and deploy them continuously to production. A constant exchange of knowledge within our analytics and data science hub, but also with product manager and stakeholders.
- Modern work philosophy: An agile development environment with pair programming, code reviews and international showcases. Use of innovative and state of the art technologies.
Your new challenges:
- You will build and deploy robust inference APIs that improve the overall quality of our existing recommendations serving layer
- Collaborate with technical and non-technical colleagues to set up and perform online experimentation of our production models (A/B testing, traffic shifting, payload logging)
- Collaborate with software/DevOps engineers, data engineers, and applied ML scientists to support tooling for enhancing monitoring and analysis of existing as well as future recommender products
What you need to bring:
- You have industry experience as a Software Engineer, Machine Learning Engineer or in an adjacent role
- You have excellent communication skills and the ability to translate business requirements into impactful and maintainable engineering solutions
- You are confident in engineering topics such as testing/monitoring/tracing, CI/CD, microservices, and provisioning of cloud managed services
- You are excited about machine learning as well as working within a cross-functional team serving company-wide product recommendations
What makes you stand out:
- You have extensive knowledge on either Python or Golang
- You have experience in building, scaling and monitoring low latency inference REST/gRPC APIs
- You have experience with Kubernetes, Istio and/or Google Cloud managed services
- You have experience with running experiments (A/B testing, multi-armed bandit) in a production environment
- You are passionate about open source projects and do actively contribute
Our tech stack:
- Google Cloud (Vertex AI/AI Platform, GCS, …)
- FastAPI, Seldon, Tensorflow/Keras
- Kubernetes (GKE), Kubeflow, Istio
- Terragrunt/Terraform, FluxCD
- Argo (Workflows/Events)
- DBT, BigQuery, ElasticSearch
- Python, Golang, Docker
Our general Benefits:
- Work-Life Balance: flexible working hours, 30 days of vacation and flexible office options (Düsseldorf, Berlin or remote). In addition, there are also childcare options in our METRO kindergartens.
- Personal growth: a comprehensive further training offer over our METRO House of Learning as well as individual development opportunities.
- Well-being: Health programs, pension scheme, regular employee events and the opportunity to participate in the annual METRO Marathon.
- Comfort: very good transport connections and free parking spaces including charging stations for e-mobility. Two canteens with delicious and discounted meals plus other catering facilities. Furthermore, discounts in our stores as well as at many partner companies.
Have we aroused your interest? Then we are looking forward to your online application. METRO is an Equal Opportunity Employer. We offer all qualified applicants full equal opportunities.
Your point of contact:
Adrian Schröter - Talent Acquisition Partner
Date posted28 March 2022
Location(s)Düsseldorf, GermanyBerlin, Germany