Principal Machine Learning Engineer

Are you a Principal Learning Engineer expert? At  , we process terabytes of data every day, and transform that data into information that powers decisions for millions of home buyers, renters, dreamers, and real estate professionals. We aim to radically simplify home buying/selling and help more people achieve the American dream on our website and mobile apps. You’ll engage with some of the best and the brightest co-workers and leaders, learn and contribute, and have a great time.

We work hard, play hard, and recognize achievement – rewarding passion for innovation, creativity, and quality. If you enjoy working in a fast-paced, dynamic, cutting-edge work environment and desire to make a meaningful contribution to the business, then make the move!

• Lead collaboration with data scientists, product managers and other cross-functional teams to build new data driven and machine learning based features for enriching the consumer experience of home shoppers, renters and sellers.
• Architect best in class solutions to maintain the machine learning lifecycle and drive ML Ops (monitor inference performance, scalability, availability etc)
• Develop predictive, explanatory models and machine learning algorithms that gracefully scale to increasing complexity as well as drive revenue growth, customer retention and support strategic decision making.
• Drive design of experiments to facilitate testing of new product and design features, with focus on improving engagement, retention, and conversion.
• Serve as a resource for the team on industry trends in algorithmic advancements, statistics and research developments.
• Take ownership and responsibility for team practices and processes and their continuous improvement.

We balance creativity and innovation on a foundation of in-person collaboration. For most roles, our employees work three or more days in our offices, where they have the opportunity to collaborate in-person, adding richness to our culture and knitting us closer together.

• Degree preferred in computer science, statistics, operations research or related fields.
• BS and 12+ years/MS and 7+ years of working on complex, scalable backend systems.
• 5+ years of industry experience deploying Machine Learning models to production at scale.
• Expertise in SQL and Python
• Expertise with AWS stack – at least a few of the following – S3, Athena, EC2, ECS, Lambda, Sage Maker, SQS, SNS, Kinesis, MongoDB, and DynamoDB
• Experience with Docker and Containerization
• Knowledgeable of core CS concepts such as: structured and unstructured data, data management and querying, common data structures and algorithms
• Strong communication, analytical, and people skills
• Experience with ML deployment APIs
• GraphQL, API Gateway, Microservices is a plus