Staff Machine Learning Engineer

Angi® is transforming the home services industry, creating an environment for homeowners, service professionals and employees to feel right at “home.” For most home maintenance needs, our platform makes it easier than ever to find a qualified service professional for indoor and outdoor jobs, home renovations (or anything in between!). We are on a mission to become the home for everything home by helping small businesses thrive and providing solutions to financing and booking home jobs with just a few clicks.  

Over the last 25 years we have opened our doors to a network of over 200K service professionals and helped over 150 million homeowners love where they live. We believe home is the most important place on earth and are embarking on a journey to redefine how people care for their homes. Angi is an amazing place to build your dream career, join us—we cannot wait to welcome you home!

About the team

Angi is seeking an exceptional Staff Machine Learning Engineer who can enable our transformation into a world-class online marketplace. The role is in our Data Science and Machine Learning team, tackling challenges such as homeowner-pro matching, search ranking, and using predictive models to optimize our product and consumer experience. This is a technical leadership role where you will apply state-of-the-art machine learning and AI techniques such as LLMs and neural rankers to both structured and unstructured data. In addition to developing models, we’re also looking for someone who can deploy them at large scale with low latencies to serve our customers dynamically.

What you’ll do

• Model Development & Data Strategy: Lead development of machine learning models and algorithms to improve our search ranking and how we match consumers with pros. Success in these areas will impact user experience & engagement, retention, and conversion rates - critical metrics for business success.
• Model Deployment & MLOps: Implement robust MLOps practices to ensure the seamless deployment and scalability of machine learning models. This includes automating model training, versioning, monitoring, and deployment processes to enable fast, reliable delivery of machine learning solutions into production environments.
• Collaboration with Cross-Functional Teams: Work closely with a strong team of engineers, data scientists, product managers, and designers to build scalable and high-impact machine learning systems. Collaborate on the end-to-end development process, from ideation to deployment, ensuring that data-driven solutions are seamlessly integrated into our products and services.
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