Staff Machine Learning Engineer - Service Intelligence

Boston, MA

Applications have closed

Wayfair Inc.

Shop Wayfair for A Zillion Things Home across all styles and budgets. 5,000 brands of furniture, lighting, cookware, and more. Free Shipping on most items.

View company page

Service Intelligence Platform is an innovative team building state-of-the-art machine learning products and platforms that are broadly utilized across our post-order customer experience. Our goal is to automate the vast majority of customer contacts with resolutions that maximize customer equity and minimize cost to serve. The team is responsible for a wide variety of NLU (Natural Language Understanding), search, recommendation, and speech related products. Our products are geared towards helping customers and agents and include goal-oriented Virtual Assistants, Automatic Speech Recognition (ASR), Q&A systems, and Recommendation in Search. 

The products that our teams work on are 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: 

  • Design and build world-class machine learning driven products using best-of-breed technologies 
  • Mentor and grow engineers on the team and across the company
  • Partner with product and engineering leadership to successfully navigate evolving business priorities
  • Collaborate with engineers and data scientists to push the  pace of innovation and experimentation by introducing best practices

What You Will Need:

  • Professional experience of building and deploying ML/AI apps to production, in realtime and batch mode at scale
  • Strong interpersonal and communication skills
  • Strong understanding of data structures, algorithms and software design concepts in streaming, REST, gRPC
  • Hands-on distributed systems compute experience 
  • Strong understanding in model inferencing lifecycle, monitoring, feedback loop and data capture in real time at scale
  • Ability to ramp up quickly on our tech stack which includes GCP, Kubernetes, Airflow, Kafka, Pandas, Scikit Learn, Pytorch, Python, and Java

About Wayfair Inc.

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.

No matter who you are, Wayfair is a place you can call home. We’re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why we’re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.

Tags: Airflow Distributed Systems Engineering GCP Kafka Kubernetes Machine Learning Pandas Python PyTorch Scikit-learn Streaming

Perks/benefits: Career development Flex vacation

Region: North America
Country: United States
Job stats:  5  1  0

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.