Twitter is what’s happening and what people are talking about right now. For us, life's not about a job, it's about purpose. We believe real change starts with conversation. Here, your voice matters. Come as you are and together we'll do what's right (not what's easy) to serve the public conversation.

Twitter's Interests Experience team is focused on helping consumers discover content that is interesting and relevant to them. We build large scale personalized recommendation engines utilizing different signals such as social network, user activity, and geolocation.

As a part of this team, you will get to solve large scale relevance and ranking problems and improve product quality. You will train new ML models, build data pipelines, do feature engineering, and perform a/b testing to launch and enable product improvements.

You have a passion for machine learning and improving the ways people consume the world, live. You’re a relevance engineer, applied data scientist or machine-learning engineer who wants to solve customer problems using Machine Learning. You’re experienced solving large scale relevance & ranking problems and comfortable building pipelines and iterating on ML models to enable future quality improvements.

• Knowledgeable in one or more of the following: machine learning, information retrieval, recommendation systems, social network analysis

• Designed and evaluated approaches for handling high-volume real-time data streams.

• Machine learning practitioner with a background in Java, Scala, or Python.

• Comfortable conducting design and code reviews.

• Effective in communicating with different functions (product, user research, design, and engineering)

Requirements:

• BS, MS, or Ph.D. in Computer Science with 4+ years of related or equivalent experience
• Experience applying personalization/recommendations research to real-world problems
• 2+ years of experience building production recommendations models, and deploying them to solve inference challenges at scale
• Good theoretical grounding in core machine learning concepts and techniques
• Familiarity with one or more deep learning software frameworks such as Tensorflow, PyTorch

A few other things we value:

• Challenge - We solve some of the industry’s hardest problems. Come to be challenged, learn, and thrive as an engineer.
• Diversity - Diversity makes us a better organization and team. We value diverse backgrounds, ideas, and experiences.
• Work, Life, Balance - We work hard, but we believe with hard work should come balance.
• Collaboration - There’s that saying, “If you want to go fast, go alone. If you want to go far, go together.” We want to go far.