Tinder-posted 7 months ago
$205,000 - $260,000/Yr
Full-time • Senior
Hybrid • Palo Alto, CA
Food Services and Drinking Places

The Engineering team is responsible for building innovative features and resilient systems that bring people together. We're always experimenting with new features to engage with our members. Although we are a high-scale tech company, the member-to-engineer ratio is very high—making the level of impact each engineer gets to have at Tinder enormous. The revenue team's mission is to monetize Tinder's global user base and increase user outcomes through subscriptions and ala-carte features. Our ML Revenue team uses machine learning driven approaches to provide tailored and best-in-class premium product offerings to our users. As a software engineer focused on Machine learning in the revenue team, you'll play a pivotal role in shaping the monetization roadmap of Tinder. Our team works on optimizing our promotions strategy, delivering the most relevant and personalized product recommendations to our users as well as supporting passive monetization efforts such as ads. As a part of our revenue ML team, you will help develop machine learning models and systems using cutting-edge technologies in causal inference, reinforcement learning, and deep learning. You'll have a unique opportunity to join a company with a global footprint while working on a team small enough for you to feel the impact each day. With Tinder's global scale and impact, you'll be at the forefront of solving some of the most complex challenges in technology.

  • Apply state-of-the-art machine learning techniques, including causal inference, reinforcement learning, deep learning and optimization in the monetization domain.
  • Leverage your expertise to optimize our promotions strategy and recommend most relevant premium products to our users.
  • Design and implement cutting-edge machine learning algorithms using deep learning frameworks and distributed data processing frameworks such as Spark.
  • Work with big data (handling 1.6B+ user swipes per day) to improve the accuracy and relevance of our prediction models.
  • Collaborate with other machine learning engineers, backend software engineers, and product managers to integrate ML models into our systems, improving user experience and driving business objectives.
  • 5+ years of experience in machine learning, with a proven track record of building models to deliver impactful solutions at scale.
  • PhD or MS in machine learning, computer science, statistics, or another highly quantitative field.
  • Experience with one or more of the following - causal inference, reinforcement learning, uplift modeling, contextual bandits, conversion rate prediction.
  • Hands-on experience in designing and building large-scale ML systems.
  • Hands-on experience in using big data batch/stream processing frameworks such as Spark and Flink.
  • Proficiency in deep learning frameworks such as PyTorch, Tensorflow, etc. as well as general purpose ML frameworks such scikit-learn and SparkML.
  • Proficiency in Python, Scala, Java or similar programming languages.
  • Hands-on experience applying machine learning in the monetization domain.
  • In-depth knowledge and understanding of deep neural networks.
  • Demonstrable experience in designing and implementing large-scale ML systems with low latency serving.
  • A strong record of publications in top conferences such as NeurIPS, ICML, and KDD.
  • A deep understanding of the scientific theory behind machine learning techniques.
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service