Software Engineer III, Machine Learning Trust and Safety

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 Trust and Safety team focuses on enhancing account authenticity, mitigating adversarial impact, building public trust, and enabling safer experiences for millions of users globally on Tinder. You will have an opportunity to work on a team that helps support one of our primary missions: ensuring that Tinder remains the safest place to meet new people.

About The Role

As a Software Engineer focused on Machine Learning Trust & Safety, you'll play a pivotal role in shaping the future of Tinder. Our Trust & Safety ML team is responsible for developing machine learning algorithms and systems to keep Tinder members safe and authentic. You'll design, implement, and scale systems that influence millions of users worldwide. You will work on cutting-edge technologies in Generative AI, Nature Language Processing (NLP), and Computer Vision (CV) to detect bad actors and content. 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 times per week. This position is located in Palo Alto, CA

In this role, you will:

Work on modeling efforts of Tinder’s Trust and Safety experiences

Apply state-of-the-art machine learning techniques, including Generative AI, CV, NLP, etc

Help the research and development of novel algorithms and models, staying at the forefront of advancements in ML technologies

Work with big data to improve the accuracy and relevance of 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

You'll need:

2+ years of hands-on experience in machine learning, with a proven track record of delivering impactful solutions at scale

PhD or MS in machine learning, computer science, statistics, or another highly quantitative field

Hands-on experience in one or more of the following - Computer Vision, NLP,  Generative AI preferably in the safety domain

In-depth knowledge of deep neural networksProficiency in deep learning frameworks such as PyTorch, TensorFlow, Keras, etc

Proficiency in Python, Java, Scala, or similar programming languages

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.

#Tinder

The salary range for this position is $165,000 - $190000.  Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of a position based in Palo Alto, CA. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.

Tinder is a global dating app that has revolutionized how people meet, growing from 1 match to one billion matches in just two years. 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.