Sr. Software Engineer, Machine Learning

Our Mission

Launched in 2012, Tinder® revolutionized how people meet, growing from 1 match to one billion matches in just two years. This rapid growth demonstrates its ability to fulfill a fundamental human need: real connection. Today, the app has been downloaded over 630 million times, leading to over 97 billion matches, serving approximately 50 million users per month in 190 countries and 45+ languages - a scale unmatched by any other app in the category. In 2024, Tinder won four Effie Awards for its first-ever global brand campaign, “It Starts with a Swipe”™"

Our Values

One Team, One Dream

We work hand-in-hand, building Tinder for our members. We succeed together when we work collaboratively across functions, teams, and time zones, and think outside the box to achieve our company vision and mission.

Own It

We take accountability and strive to make a positive impact in all aspects of our business, through ownership, innovation, and a commitment to excellence.

Never Stop Learning

We cultivate a culture where it’s safe to take risks. We seek out input, share honest feedback, celebrate our wins, and learn from our mistakes in order to continue improving.

Spark Solutions

We’re problem solvers, focusing on how to best move forward when faced with obstacles. We don’t dwell on the past or on the issues at hand, but instead look at how to stay agile and overcome hurdles to achieve our goals.

Embrace Our Differences

We are intentional about building a workplace that reflects the rich diversity of our members. By leveraging different perspectives and other ways of thinking, we build better experiences for our members and our team.

The Team

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.

About The Role

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.

Where you'll work

This is a hybrid role and requires in-office collaboration three days per week. This position is located in Palo Alto, CA.

• 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 domainIn-depth knowledge and understanding of deep neural networks.
• Demonstrable experience in designing and implementing large-scale ML systems with low latency servingA strong record of publications in top conferences such as NeurIPS, ICML, and KDDA deep understanding of the scientific theory behind machine learning techniques.

Commitment to Inclusion

At Tinder, we don’t just accept difference, we celebrate it. We strive to build a workplace that reflects the rich diversity of our members around the world, and we value unique perspectives and backgrounds. Even if you don’t meet all the listed qualifications, we invite you to apply and show us how your skills could transfer. Tinder is proud to be an equal opportunity workplace where we welcome people of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. Learn more here: https://www.lifeattinder.com/dei

If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please speak to your Talent Acquisition Partner directly.

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