Senior Software Engineer - Machine Learning
We are seeking world-class machine learning experts to join our engineering team. You will be working with a team of talented engineers and researchers to develop core machine learning algorithms for improving the unique user experience available only with us. You will have tons of responsibility, freedom and an opportunity to have a direct and immediate impact on company growth. We would love to talk to you if you are passionate about helping our users achieve more matches, communicate more effectively, and create more love at a truly global scale.
This is a full-time position based in our offices in Palo Alto, CA and Los Angeles, CA.
In this Machine Learning role, you will:
Personal Recommendation. The user experience with us is unique and highly personalized. You’ll apply a range of algorithms to personalize recommendations in feed, from the latest in Neural Nets, to collaborative filtering, to explore/exploit approaches, such as Multi-armed Bandits, to bring the highest quality dating experience to tens of millions of users.
Anti-Spam. Now that we have more than 100 million users in over 190 countries, we have some unique challenges in protecting our ecosystem from spammers. How do you model spammer or bot behavior with different intents? How do you detect a botnet stealing our users profile information?
Image Understanding. We hosts hundreds of millions of profile pictures. A better understanding of images will not only help us avoid inappropriate content, but also understand user interests and preferences in absence of explicit user input. The state-of-the-art computer vision techniques, such as Convolutional Neural Nets (CNN), will be applicable here.
Dialogue Understanding. People talk after they match. How do you suggest conversation topics to break the ice? Can we detect when a dialogue goes awry? There are huge opportunities for natural language processing with us.
We’re looking for:
As part of our team, you’ll enjoy:
San Jose, San Francisco Ca
Phone: 866 816-1615 x 823