Software Engineer II

Wayfair’s Search and Recommendations team builds the core platforms and services that allow our customers to discover & buy the products they love. Just last year alone our team has contributed to hundreds of millions in incremental revenue. We do this by leveraging Wayfair’s extensive customer and product data to deliver trusted and valuable recommendations in real‑time using custom machine learning models.

We productionalize these ML models as microservices and build data pipelines necessary for inference and model training.

Our platforms and services are used to power experiences for search, browse across multiple storefront and marketing channels and are called over a billion times a day.

We’re looking for an experienced senior software engineer to join our highly impactful team to help us build and extend our Search and Browse Platform. A Software Engineer will be responsible for high quality implementation and consistent maintenance of systems that support the ranking of products for keyword search on Wayfair’s sites. We have ambitious goals to improve this search functionality to better understand customer intent and improve our ability to rank products for them, regardless of the page they are browsing.

• Work with a broader highly collaborative cross‑functional team that includes product managers, data scientists, and analysts.
• Work with a variety of technologies, including Java, Spark, Kafka, Aerospike, Hadoop, Airflow, RESTful web services, gRPC, Kubernetes. Additionally, you’ll work with various managed GCP offerings like Big Query, Composer and Vertex AI.
• Build platforms and services that allow us to make real‑time ML powered decisions that improve the customer’s onsite search experience.
• Deliver direct measurable results for our business and customers through improved product recommendations.
• Mentor junior engineers to develop the next generation of Wayfair engineering.
• Provide high quality code and technical design reviews.
• Contribute to the code base, with a mind to best practices and an equally high degree of autonomy.

• A Bachelor’s Degree in Computer Science, Data Science, or a related engineering discipline.
• At least 2 years of relevant industry experience.
• 3+ years of experience in a modern programming language, preferably Java.
• Experience with Lucene-based Search engines like Elasticsearch.
• Experience developing and designing scalable distributed systems with deep understanding of object oriented design and design patterns.
• Experience designing APIs and microservices.
• Experience building high performance, scalable and fault‑tolerant Java applications preferred.
• Experience working on cloud technologies specifically GCP is a plus.
• Experience with building and maintaining highly available, production ML systems at scale.
• Experience with large scale data processing using big data technologies like Hadoop, Spark and Google Biq Query is a plus.
• Experience using Kubernetes, Docker, Buildkite, and Terraform for containerization and CI/CD is a plus.
• Experience with streaming technologies like Kafka, Flink are a plus.
• Excellent communication skills and ability to work effectively with engineers, product managers, data scientists, analysts and business sta

Wayfair is fully committed to providing equal opportunities for all individuals, including individuals with disabilities. As part of this commitment, Wayfair will make reasonable accommodations to the known physical or mental limitations of qualified individuals with disabilities, unless doing so would impose an undue hardship on business operations. If you require a reasonable accommodation to participate in the job application or interview process, please let us know by completing our Accommodations for Applicants form.

For more information about applying for a career at Wayfair, visit our FAQ page here.

Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes.…