Tinder
Sr. Software Engineer, Machine Learning Revenue
Tinder, Palo Alto, California, United States, 94306
Sr. Software Engineer, Machine Learning Revenue
Join to apply for the
Sr. Software Engineer, Machine Learning Revenue
role at
Tinder .
Base pay range $205,000/yr – $260,000/yr
Our Mission Launched in 2012, Tinder revolutionized the way people meet, growing from 1 match to one billion matches in just two years. Today, the app has been downloaded over 630 million times, leading to more than 97 billion matches, serving approximately 50 million users per month across 190 countries and 45+ languages. In 2024, Tinder won four Effie Awards for its 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 collaborate across functions, teams, and time zones, and think outside the box to achieve our vision and mission.
Own It – We take accountability and strive to make a positive impact through ownership, innovation, and a commitment to excellence.
Spark Solutions – We’re problem solvers, focusing on how to move forward when faced with obstacles. We don’t dwell on the past; we stay agile to achieve our goals.
Embrace Our Differences – We build a workplace that reflects the diversity of our members, leveraging different perspectives to create better experiences.
The Team The Engineering team is responsible for building innovative features and resilient systems that bring people together. The revenue team’s mission is to monetize Tinder’s global user base and increase user outcomes through subscriptions and a‑la‑carté features. Our ML Revenue team uses machine learning to deliver tailored, best‑in‑class premium product offerings to users.
About The Role As a software engineer focused on machine learning in the revenue team, you’ll play a pivotal role in shaping Tinder’s monetization roadmap. The team works on optimizing promotions strategy, delivering the most relevant and personalized product recommendations, and supporting passive monetization efforts such as ads. You’ll develop machine learning models and systems using cutting‑edge technologies in causal inference, reinforcement learning, and deep learning.
Where you'll work This is a hybrid role requiring in‑office collaboration three days per week. The position is located in Palo Alto, CA.
In this role, you will:
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 the most relevant premium products to 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 1.6 B+ 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.
You’ll need:
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 designing and building large‑scale ML systems.
Hands‑on experience using big‑data batch/stream processing frameworks such as Spark and Flink.
Proficiency in deep‑learning frameworks such as PyTorch, TensorFlow, as well as general‑purpose ML frameworks such as scikit‑learn and SparkML.
Proficiency in Python, Scala, Java or similar programming languages.
Nice to have:
Hands‑on experience applying machine learning in the monetization domain.
In‑depth knowledge and understanding of deep neural networks.
Demonstrable experience designing and implementing large‑scale ML systems with low latency serving.
A strong record of publications in top conferences such as NeurIPS, ICML, and KDDA, and deep understanding of the scientific theory behind machine learning techniques.
As a full‑time employee, you’ll enjoy:
Flexible vacation (no waiting period) and 10 annual wellness days.
Time off to volunteer and charitable donation matching.
Comprehensive health, vision, and dental coverage.
100% 401(k) employer match up to 10%, Employee Stock Purchase Plan (ESPP).
100% paid parental leave (including for non‑birthing parents), family‑forming benefits, and Milk Stork for business travel, surrogacy, and relocation.
Mentorship through MentorMatch program, access to 6,000+ online courses via Udemy, and an annual professional‑development stipend.
Mental‑health support via Modern Health, concierge medical membership, pet insurance, fitness membership subsidy, and commuter subsidy.
Free premium subscriptions for several Match Group apps – including Tinder Platinum.
Commitment to Inclusion At Tinder, we celebrate difference and encourage an inclusive workplace that reflects the diversity of our members worldwide. We welcome candidates of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. Even if you don’t meet all listed qualifications, we invite you to apply and show how your skills could transfer. Learn more at https://www.lifeattinder.com/dei.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are made by humans. If you would like more information about how your data is processed, please contact us.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Software Development, Consumer Services, and Technology, Information and Internet
#J-18808-Ljbffr
Sr. Software Engineer, Machine Learning Revenue
role at
Tinder .
Base pay range $205,000/yr – $260,000/yr
Our Mission Launched in 2012, Tinder revolutionized the way people meet, growing from 1 match to one billion matches in just two years. Today, the app has been downloaded over 630 million times, leading to more than 97 billion matches, serving approximately 50 million users per month across 190 countries and 45+ languages. In 2024, Tinder won four Effie Awards for its 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 collaborate across functions, teams, and time zones, and think outside the box to achieve our vision and mission.
Own It – We take accountability and strive to make a positive impact through ownership, innovation, and a commitment to excellence.
Spark Solutions – We’re problem solvers, focusing on how to move forward when faced with obstacles. We don’t dwell on the past; we stay agile to achieve our goals.
Embrace Our Differences – We build a workplace that reflects the diversity of our members, leveraging different perspectives to create better experiences.
The Team The Engineering team is responsible for building innovative features and resilient systems that bring people together. The revenue team’s mission is to monetize Tinder’s global user base and increase user outcomes through subscriptions and a‑la‑carté features. Our ML Revenue team uses machine learning to deliver tailored, best‑in‑class premium product offerings to users.
About The Role As a software engineer focused on machine learning in the revenue team, you’ll play a pivotal role in shaping Tinder’s monetization roadmap. The team works on optimizing promotions strategy, delivering the most relevant and personalized product recommendations, and supporting passive monetization efforts such as ads. You’ll develop machine learning models and systems using cutting‑edge technologies in causal inference, reinforcement learning, and deep learning.
Where you'll work This is a hybrid role requiring in‑office collaboration three days per week. The position is located in Palo Alto, CA.
In this role, you will:
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 the most relevant premium products to 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 1.6 B+ 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.
You’ll need:
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 designing and building large‑scale ML systems.
Hands‑on experience using big‑data batch/stream processing frameworks such as Spark and Flink.
Proficiency in deep‑learning frameworks such as PyTorch, TensorFlow, as well as general‑purpose ML frameworks such as scikit‑learn and SparkML.
Proficiency in Python, Scala, Java or similar programming languages.
Nice to have:
Hands‑on experience applying machine learning in the monetization domain.
In‑depth knowledge and understanding of deep neural networks.
Demonstrable experience designing and implementing large‑scale ML systems with low latency serving.
A strong record of publications in top conferences such as NeurIPS, ICML, and KDDA, and deep understanding of the scientific theory behind machine learning techniques.
As a full‑time employee, you’ll enjoy:
Flexible vacation (no waiting period) and 10 annual wellness days.
Time off to volunteer and charitable donation matching.
Comprehensive health, vision, and dental coverage.
100% 401(k) employer match up to 10%, Employee Stock Purchase Plan (ESPP).
100% paid parental leave (including for non‑birthing parents), family‑forming benefits, and Milk Stork for business travel, surrogacy, and relocation.
Mentorship through MentorMatch program, access to 6,000+ online courses via Udemy, and an annual professional‑development stipend.
Mental‑health support via Modern Health, concierge medical membership, pet insurance, fitness membership subsidy, and commuter subsidy.
Free premium subscriptions for several Match Group apps – including Tinder Platinum.
Commitment to Inclusion At Tinder, we celebrate difference and encourage an inclusive workplace that reflects the diversity of our members worldwide. We welcome candidates of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. Even if you don’t meet all listed qualifications, we invite you to apply and show how your skills could transfer. Learn more at https://www.lifeattinder.com/dei.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are made by humans. If you would like more information about how your data is processed, please contact us.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Software Development, Consumer Services, and Technology, Information and Internet
#J-18808-Ljbffr