We’re looking for a Principal Software Engineer to lead our Data Science Enablement and MLOps initiatives. As a data-driven company, Data Science and MLOps are crucial to our overall business strategy and we have a large, cross-functional team excited about adopting enabling technologies. 

The Principal Engineer of ML Ops will contribute to the vision, drive the architecture, build solutions, and advocate for the adoption of ML Ops and other Data Science enablers. 

Consumers are our north star and we aim to provide buyers, owners, sellers, and renters with best-in-class experiences built on a modern cloud-based, tech stack. The role will be part of a diverse and multi-disciplinary pool of engineering and technology talent working in close partnership with Data Science and Product.

 What You’ll  do

• Design, build, and maintain our Data Science enablers and ML Ops solution, covering the entire spectrum of technology including automation, monitoring, and model serving among others
• Drive adoption and evangelize solutions to Product, Data Science  and Engineering.
• Coach, mentor, and guide colleagues to deliver the best solution keeping in mind return on investment and total cost of ownership
• Drive sound decision-making processes to ensure the right technology choices are made for implementing solutions; conduct alternative analysis for technology selection or build vs buy decisions and present to stakeholders
• Partner with product managers and Data Science leaders to shape product definition so that it can be built in flexible, extensible, and robust way; work collaboratively across teams to plan and execute at high velocity
• Collaborate with technical leads and architects to define a technical roadmap and maintain the overall architectural integrity of the suite of Data Science enablers; drive and support innovation by acting as a sounding board for ideas and help bring them to life
• Construct and maintain an environment and culture of integrity, trust, feedback, and continuous improvement
• Understand Data Science strategies of Realtor.com and partner with multiple teams to define technology roadmap
• Actively seek out new technologies, evaluate them and make recommendations to integrate them into our solutions and products
• Actively promote a culture of inclusion and teamwork 

About You

• 15+ years experience in relevant fields (Building large-scale web applications, web services, data pipelines, etc.)
• Experience training and deploying ML models to production
• Experience building and maintaining ML Pipelines.
• Knowledge of Data Science and the Model Development Lifecycle.
• Experience driving improvement in software engineering practices/architectural skills (coding standards, code reviews, continuous integration, etc.)
• Passion for software development with hands-on experience in the Data Science ecosystem
• Comfortable with cloud-based architectures, development, and deployment
• Experience with build, test and deployment automation technologies
• Experience monitoring for SLAs, alerting, and remediating service disruptions
• Experience bridging the gap between engineering and data science groups
• Deep expertise in one or more of the languages we commonly use - Python, Java, Scala, and/or JavaScript/TypeScript.
• A strong results and outcome-driven focus, understanding the value derived from rapidly shipping solutions and learning/iterating on the results
• Well-developed communication and interpersonal skills, connecting directly and effectively with cross-functional stakeholders at various levels
• Able to coach and mentor engineers, helping them develop their skills and advance their careers.
• A lifelong learner
• A Bachelors or Masters degree in Computer Science/Engineering or a related field, or equivalent professional experience