Senior Software Engineer, Machine Learning Infrastructure Full-time

A home is the biggest investment most people make, and yet, it doesn’t come with a manual. We’re building the only app homeowners need to effortlessly manage their homes – knowing what to do, when to do it, and who to hire. Millions of people care for what matters most, and professionals earn billions of dollars through our platform. As one of the fastest-growing companies in a $600B+ industry, we must be doing something right.

We are driven by a common goal and the deep satisfaction that comes from knowing our work supports local economies, helps small businesses grow, and brings homeowners peace of mind. We’re seeking people who continually put our purpose first: advocating for professionals and customers, embracing change, and choosing teamwork every day.

We’re creating a new era of home care. If making an impact and the chance to do good inspires you, join us. Imagine what we’ll build together.
About the Machine Learning Infrastructure Team

Our challenges span a wide variety of areas, ranging from building search, ranking & recommendations systems to optimizing pricing and spam detection models. The ML Infrastructure team is responsible for centralizing, standardizing, and evolving machine learning infrastructure capabilities for teams across engineering that experiment with or deploy machine learning models for different problems.
About the Role

As a Senior Software Engineer focused on ML Infrastructure, you’ll bring our ML Infrastructure vision to life. You’ll collaborate with engineers, applied scientists, and product managers across engineering to refine and execute our shared vision for generative AI, feature platforms, model deployment, and model monitoring. This could include introducing the latest feature engineering & model building frameworks, creating a standardized process for model deployment and monitoring, working with the data platform team on evolving feature storage, or working with applied scientists on productization of complex models.
Responsibilities

• Collaborate with engineers, applied scientists, and product managers to identify shared ML infrastructure needs across areas like feature engineering, model experimentation, model inference & CI/CD, generative AI, and model monitoring.
• Build, maintain, and communicate our roadmap.
• Centralize and standardize ML infrastructure & associated best practices for product teams across engineering.
• Experiment with and introduce next-generation ML infrastructure capabilities and frameworks.
• Drive projects to completion with a tenacious focus on the business impact.
• Solve tough technical problems and stay up-to-date with the latest advances in this constantly evolving problem space.

What You’ll Need

If you don’t think you meet all of the criteria below but are still interested in the job, please apply. Nobody checks every box, and we’re looking for someone excited to join the team.

• 5+ years of industry experience in engineering.
• 2+ years of industry experience working on machine learning modeling or infrastructure.
• Proficiency in at least one major programming language with the ability to switch between multiple languages. We use Go and Python most heavily.
• Experience building software on top of relational databases such as Postgres or MySQL.
• Ability to break down complex problems rigorously and understand the tradeoffs necessary to deliver great, impactful products.
• Curiosity, data-driven mindset, love for asking questions, and critical thinking about problems.
• Passion for delivering value to users and teammates through your work.

Bonus Points

• Experience building and evolving machine learning infrastructure.
• Familiarity with frameworks like PyTorch, TensorFlow, Scikit-learn, and Airflow.
• Experience with generative AI infrastructure and vendors.
• Experience building and maintaining reliable, performant distributed systems.
• Familiarity with major cloud providers and/or the big data ecosystem (Amazon Web Services, Google Cloud Platform, Spark, etc).
• Ability to thrive in a fast-paced startup environment.

Benefits & Perks

• Virtual-first working model coupled with in-person events.
• 20 company-wide holidays including a week-long end-of-year company shutdown.
• Library (optional use collaboration & connection hub) in San Francisco.
• WiFi reimbursements.
• Cell phone reimbursements (North America).
• Employee Assistance Program for mental health and well-being.

Learn More About Us

• Life @ Our Company Blog
• How We Are Embracing Virtual Work
• Follow us on LinkedIn
• Meet the Pros Who Inspire Us

We embrace diversity and are proud to be an equal opportunity workplace. We do not discriminate based on sex, race, color, age, pregnancy, sexual orientation, gender identity or expression, religion, national origin, ancestry, citizenship, marital status, military or veteran status, genetic information, disability status, or any other characteristic protected by federal, provincial, state, or local law. We will also consider for employment qualified applicants with arrest and conviction records, consistent with applicable law.