Staff Machine Learning Engineer

Position Overview

Angi® is seeking an exceptional Staff Machine Learning Engineer to join our Data Science and Machine Learning team. This role is pivotal in our transformation into a world-class online marketplace, focusing on challenges such as homeowner-pro matching, search ranking, and optimizing product and consumer experience through predictive models. You will apply state-of-the-art machine learning and AI techniques, including LLMs and neural rankers, to both structured and unstructured data. A key aspect of this role involves deploying these models at large scale with low latencies to serve our customers dynamically.

About Angi®

At Angi®, our mission for 30 years has been simple: get jobs done well. We achieve this by connecting homeowners with reliable, skilled professionals and by connecting these professionals with homeowners who need their services.

Angi at a glance:

• A new homeowner turns to Angi every second.
• Our network boasts over 150,000 skilled pros across more than 50 service categories.
• Over 150,000,000 projects have been brought to Angi, and this number continues to grow.

Why join Angi: Angi® is shaping the future of the home services industry, creating an environment where homeowners, service professionals, and employees all benefit from more jobs done well. Our platform simplifies the process for homeowners to find skilled pros for any home need, while serving as a valuable business partner for pros looking to grow their business. We believe home is the most important place on earth and are dedicated to making a real impact on families, communities, and livelihoods. Angi is an amazing place to call home, and we look forward to welcoming you.

About the Team

The Data Science and Machine Learning team at Angi is focused on tackling complex challenges within our marketplace. We work on critical areas like optimizing homeowner-pro matching, enhancing search ranking algorithms, and leveraging predictive models to improve our product and customer experience.

Responsibilities

• Model Development & Data Strategy: Lead the development of machine learning models and algorithms to enhance search ranking and improve the matching of consumers with pros. Success in these areas directly impacts user experience, engagement, retention, and conversion rates – key metrics for business success.
• Model Deployment & MLOps: Implement robust MLOps practices to ensure seamless deployment and scalability of machine learning models. This includes automating model training, versioning, monitoring, and deployment processes for 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, high-impact machine learning systems. You will collaborate on the end-to-end development process, from ideation to deployment, ensuring data-driven solutions are seamlessly integrated into our products and services.
• Innovation: Foster innovation within the team by exploring new approaches and techniques to solve complex business problems.
• Mentorship: Guide junior team members and cultivate a culture of continuous learning and technical excellence. Lead and encourage innovation and knowledge sharing to enhance the team's capabilities in advanced machine learning techniques from both industry and academia.

Requirements

• Master’s or Ph.D. in a quantitative field (e.g., Computer Science, Statistics, Mathematics, or related fields).
• 7+ years of experience in data science & machine learning, with a focus on real-time ML models, preferably within the tech industry and marketplace environments.
• Expertise in machine learning and deep learning, with good working knowledge of large language models (LLMs).
• Proven track record of deploying highly impactful machine learning models into production environments.
• Proficiency in SQL and Python.
• Experience with cloud ML solutions.
• Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Salary

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Location Type

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Employment Type

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