Senior Machine Learning Engineer at Wayfair
🇩🇪 Germany › Berlin (Posted Mar 12 2022)
About the company
Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston or Berlin, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you’re looking for rapid growth, constant learning, and dynamic challenges, then you’ll find that amazing career opportunities are knocking.
Wayfair’s EU Data Science team builds the algorithmic systems that drive our business.
The team has a wide range of scope: Supply Chain and Operations, Fraud detection, Customer Feedback and Translations. As a result, we work with several different engineering teams in different departments for our model productization.
As a Machine Learning Engineer, you will partner both with those teams and our Data Science tech leads to productionize cutting-edge models for Supply Chain and Operations in customer-facing scenarios providing significant business-impact.
You will thus join our Staff Machine Learning engineering to build out the supply chain and operations area which is one of the newest global domains of Wayfair’s Data Science Team run from our Berlin office.
You will do so by partnering with the various engineering teams across Wayfair and tech leads in our Data Science team and thus build the bridge from Data Science model development to the integration into our engineering infrastructure.
The projects that our teams work on vary in maturity, but are often built from the ground up – we look for entrepreneurial individuals who want to take ownership over their own agenda and thrive in a collaborative team environment.
What You'll Do:
You’ll be part of one of our Data Science teams, being a key player contributing to solve challenging problems on data-driven scenarios using Machine Learning at scale
Deploy and maintain production models and services using both internal and open-source tools
Collaborate closely with the science and engineering teams of supply chain, fraud, user generated content and merchandising to ensure integration of our machine learning models into our microservices architecture
Improve the pace of innovation and experimentation by introducing best practices and tools for Data Science workflow, code quality and DevOps
Architect and write code to implement high-quality, scalable services with effective system boundaries that supports our long term vision & strategy
Lead your teammates by example, as a senior member of the team your code and system designs demonstrate the path the team should follow
Contribute to and influence our technology and product strategy and roadmaps
Develop GCP based solutions within the EU Data Science team and help establish our team as the center of excellence for GCP.
What You'll Need:
Bachelor’s Degree in Computer Science or related field
6+ years of previous experience in Software Engineering with industry experience in Machine Learning
Familiarity with Data & ML processing pipelines, experience with implementation in low-latency real-time platforms and/or scalable offline batch processes
Solid experience with Python (production level code) and SQL
Job scheduling technologies (i.e. Airflow) and containerization for isolated development (Docker, Kubernetes) shouldn’t be foreign concepts to you.
Knowledge of Microservice architectures.
Capability to communicate and collaborate across the wider organization, influencing decisions without direct authority and always with inclusive, adaptable and persuasive communication.
A passion for challenging problems and the ability to work with many different teams identifying architectural boundaries and platform interfaces.
Desire to always be learning, and a collaborative team-player attitude!
Nice to have would be some experience with:
Familiarity with Google Cloud Platform (also good if familiar with AWS or Azure)
Proficiency in Big Data and Streaming tech (Spark/Flink, Kafka, or similar)
Experience using other programming languages than Python in production
Previous exposure to Supply Chain, Fraud, Payments, or NLP projects
Experience with leveraging a ML Platform such as Google Vertex AI, AWS Sagemaker, etc
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