At Angi, we have one simple mission: Get all your home service jobs done well. That’s how we’ve helped over 150 million homeowners care for their homes over the last 25+ years. Today, our network has grown to over 200,000 skilled local pros — and our platform has made it easier than ever to find the right one for your project, from repairs to renovations and everything in between.

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.
• Innovation: Foster innovation within the team, exploring new approaches and techniques to solve complex business problems.
• Mentorship: Guide junior team members and foster 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.

Who you are

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

We value diversity

We know that the best ideas come from teams where diverse points of view uncover new solutions to hard problems. We welcome and value individuals who bring diverse life experiences, educational backgrounds, cultures, and work experiences.

Compensation & Benefits

• The salary band for this position ranges from $200,000 - $280,000 commensurate with experience and performance. Compensation may vary based on factors such as cost of living. 
• This position will be eligible for a competitive year end performance bonus & equity package. 
• Full medical, dental, vision package to fit your needs 
• Flexible vacation policy; work hard and take time when you need it 
• Pet discount plans & retirement plan with company match (401K) 
• The rare opportunity to work with sharp, motivated teammates solving some of the most unique challenges and changing the world 

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