Zalando
Sr/Principal Applied Scientist
Skills
2 months ago
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Important information
Contract type:
Permanent
Location:
Shenzhen, Guangdong Province, China
Work mode:
Onsite
Published on:
19 August 2026
What they need
WHERE YOUR EXPERTISE IS NEEDED
1,Responsible for applied science initiatives in the fashion e-commerce domain, encompassing research strategy, roadmap planning, and project execution.
2,Focused on user-centric needs, leveraging AI and large language model (LLM) technologies to establish a cutting-edge domain-specific knowledge platform, drive intelligent content creation, and develop smart assistant solutions that innovate user interaction experiences.
3,Take end-to-end ownership for developing, deploying, and operating machine learning solutions on our centralized abuse protection platform for detecting and managing transactional risks
4,Raise the analytical and technical bar within the applied science domain by improving processes and documentation
5,Quick prototyping and spiking of machine learning models to assess their applicability for solving research, customer, and business problems
6,Tackle challenges for developing algorithms and running them efficiently on resource constrained platforms
7,Rigorous approach in solving, conducting, and documenting research projects
8,Work in a cross functional team consisting of software applied scientists, engineers, product managers, and product analysts
9,Contribute to our growing science community and encourage knowledge sharing in an agile work environment
WHAT WE’RE LOOKING FOR:
1,Solid hands-on experience as an applied scientist, developing and productionizing machine / deep learning models in cloud environments (preferably AWS)
2,Proficient in large model frameworks such as Llama/Qwen and their applications, with solid experience in prompt engineering. Skilled in conducting supervised fine-tuning (SFT) and knowledge enhancement by integrating domain-specific data
3,Good proficiency in Python and related machine / deep learning frameworks, such as Pytorch, Tensorflow, Keras, etc.
4,Expertise in machine learning infrastructure and tooling, such as Databricks, Spark, Flink, relational databases, AWS SageMaker, S3, EC2, Step Functions, Git
5,Experience with data storage, ingestion, and transformation, also including machine learning workflow orchestration
6,Passion for developing clean, well maintainable, and testable code
Motivation for continued personal development in discovering new technologies and software services
7,Curiosity and eagerness to understand the business context where the team operates and the customer problems being solved
8,Very good communication skills to translate (even complex) analytical / engineering decisions and outcomes to broader, non-technical audience
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