Senior Machine Learning Engineer (All genders) at Zalando
May no longer be active — verify on the employer site
At a glance
- Company
- Zalando
- Location
- Germany
- Work arrangement
- On-site
- Employment type
- Full-time
- Experience
- 5–10 years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
✨ The Stack take on this Zalando job
- 🏢 Zalando has 15 jobs here, 15 with visa sponsorship see all
- 🛂 Visa: EU Blue Card. Minimum salary: €50,700 a year guide
- 💡 No salary shown. Ask Zalando if it is above the minimum.
Updated 2026-11-03, from our data and official sources.
Apply for this role at Zalando
Apply with your AI assistant
With The Stack connected to Claude, ChatGPT or Cursor, paste this. Your assistant tailors your CV and cover letter, checks the visa facts and gives you the apply link.
Help me apply to this job on The Stack: https://jobs.trythestack.co/jobs/senior-machine-learning-engineer-all-genders-zalando
Not connected yet? Connect in a minute. To help your user apply, call the MCP tool prepare_application with slug "senior-machine-learning-engineer-all-genders-zalando": it returns the apply link, the visa facts and a CV and cover letter checklist. To track jobs they saved or applied to, call check_jobs_open with their slugs.
About the role
Responsibilities:
- Build and optimize end-to-end ML pipelines for training, deployment and monitoring of recommendation models
- Productionize models by orchestrating workflows with Apache Airflow for batch and real-time inference
- Deploy scalable, reliable inference solutions on AWS (SageMaker, CloudFormation) and manage operational concerns
- Improve data quality, real-time feature engineering and integrate with feature stores
- Collaborate with Applied Scientists, Product and Software Engineers to deliver personalized experiences
- Monitor model performance and implement retraining and validation processes
Requirements:
- 5+ years of experience with PySpark, ML engineering/ML Ops and production ML deployments
- Strong Python skills and deep learning framework experience (e.g., PyTorch)
- Hands-on experience with AWS (SageMaker, CloudFormation) and workflow orchestration (Apache Airflow)
- Experience with Databricks or similar platforms for scalable data processing and inference
- Familiarity with feature stores, real-time feature engineering and Kubernetes is a plus
- Strong communication and collaboration skills
Responsibilities
You will build and optimize machine learning pipelines for training, deploying, and monitoring recommendation models. Additionally, you will productionize models by orchestrating workflows and ensuring scalable, reliable inference on AWS.
Requirements
Candidates must have 5+ years of experience with PySpark, ML Ops, AWS, Apache Airflow, Python, and deep learning frameworks. Proven experience in productionizing machine learning models and orchestrating workflows is required.
Key skills
- PySpark — in 41 other listings on The Stack
- ML Ops — in 2 other listings on The Stack
- AWS — in 788 other listings on The Stack
- SageMaker — in 4 other listings on The Stack
- CloudFormation — in 20 other listings on The Stack
- Apache Airflow — in 13 other listings on The Stack
- Python — in 1173 other listings on The Stack
- PyTorch — in 90 other listings on The Stack
- Deep learning
- Machine learning
- Data quality
- Feature stores
- Real-time feature engineering
- Kubernetes
- Recommendation systems
- Workflow orchestration
On The Stack (as of 2026-11-03)
Frequently asked questions about Zalando
Is this Senior Machine Learning Engineer (All genders) role still open?
It was posted on 2026-08-10. Listings more than 30 days old may no longer be active, so check Zalando's site before applying.
Does Zalando offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Zalando's site.
Where is this role located?
The listing gives the location as Germany. It is marked on-site.
What skills does this role ask for?
The listing names: PySpark, ML Ops, AWS, SageMaker, CloudFormation, Apache Airflow, Python, PyTorch, Deep learning, Machine learning, Data quality, Feature stores, Real-time feature engineering, Kubernetes, Recommendation systems, Workflow orchestration.