Engineering Manager – Machine Learning Infrastructure – Tinder
Dev Ops & SysAdmin
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Tinder (501+ Employees, 14% 2 Yr Employee Growth Rate)
15% 1-Year Employee Growth Rate | 14% 2-Year Employee Growth Rate | LinkedIn | $50M Venture Funding
What Is Employee Growth Rate & Why Is It Important?
Tinder brings people together. With tens of millions of users, hundreds of millions of downloads, 2+ billion swipes per day, 20+ million matches per day and a presence in 190+ countries, our reach is expansive—and rapidly growing. Machine learning plays a critical role at Tinder. We have many machine learning models in production that power product features like recommendations, trust and safety, revenue and engagement optimization, etc. We adopt a variety of large scale algorithms – from linear models to decision trees to deep neural networks.
The ML Infrastructure team develops infrastructures and systems that support end-to-end machine learning development cycle, including training, serving, feature management, model management, monitoring and observability, etc. We are looking for an Engineering Manager who will lead this team to enable and empower all ML projects at Tinder.
In this role, you will:
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- Grow and lead a team of engineers to build infrastructure that best supports the needs of machine learning across all Tinder engineering.
- Design and build ML infrastructure with high scalability, availability, usability, and maintainability while maintaining correctness, interpretability and experimentation
- Collaborate with software engineers, data engineers in building product features
- Build effective partnerships to achieve high impact objectives
- Drive strategic plans and tactical execution that align with business goals
- Establish best practices in ML and data engineering
- Lead and mentor team members to reach their full potential
Who you are:
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- 5+ years of machine learning Infrastructure or Engineering experience
- 3+ years of technical leadership experience
- Hands on experience architecting, building, and maintaining large-scale, end-to-end machine learning systems
- Passion for taking initiatives and driving high leverage solutions in a rapidly-changing environment
- Wisdom on technical trade offs, strong sense of ownership and execution
- Ability to inspire and motivate the team to go above and beyond
Bonus points if you have,
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- M.S., or Ph.D. in Computer Science, or equivalent
- Experience in AWS ML stack and Tensorflow serving
As part of our team, you’ll enjoy:
• Working on a product that has an immediate impact on people’s lives all around the world
• Collaborating with a team of creative, fun and driven colleagues
• Comprehensive health coverage, competitive salary, 401(k) employer match, Employee Stock Purchase Plan (ESPP)
• Other perks and wellness benefits like a fitness membership subsidy, paid concierge medical membership, pet insurance offerings, and a commuter subsidy
• A robust Learning + Development offering including our MentorMatch program, access to a library of 6,000+ online learning courses through Udemy, and an annual L+D stipend
• Access to mental health resources
• Fertility preservation benefits
• No Meeting Wednesdays and access to a wide range of product and service discounts through Perkspot
• Charitable donations match up to $15,000 annually
• Monthly and weekly interactive virtual events including Book Club, trivia with prizes and yoga workouts
• The opportunity to join six active Employee Resource Groups (ERGs)
At Tinder, we don’t just accept difference — we celebrate it, we support it, and we thrive on it for the benefit of our employees, our product, and our community. We strive to make our workplace an inclusive and diverse environment, giving people from all walks of life the opportunity to have a voice. We champion and encourage those who bring different perspectives, ideas, and creativity to join our team dedicated to bringing people together across the globe. Tinder is proud to be an equal opportunity workplace where we welcome all people regardless of sex, gender identity, race, ethnicity, disability, or other lived experience.