Senior Software Engineer, Tinder
Machine Learning Infrastructure
$220-250k
3 days a week in office (Palo Alto, CA)
Swipe-based dating app
Be an early applicant
Swipe-based dating app
1001+ employees
Be an early applicant
$220-250k
3 days a week in office (Palo Alto, CA)
1001+ employees
Company mission
To power and inspire real connections by making meeting easy and fun for every new generation of singles.
Role
Who you are
- Bachelor’s degree in Computer Science, Engineering, Technology, or a related field
- 5+ years of experience building or operating ML platforms, including training, serving, feature management, or experimentation systems
- Hands-on experience designing, building, or running feature stores at scale
- Strong software engineering fundamentals, with proficiency in Python and at least one of Java, Scala, Go, or a similar language
- Practical experience with ML serving platforms such as Triton, Ray Serve, or Seldon
- Solid grasp of core machine learning concepts, including model training, evaluation, validation, and performance measurement
- Proven ability to lead cross-functional initiatives and work effectively across ML, infrastructure, and product teams
- Deep experience in distributed systems, cloud infrastructure, and MLOps, with hands-on exposure to transformers and modern deep learning architectures
- Ability to bridge the gap between cutting-edge ML research and reliable, production-grade systems
What the job involves
- Our ML Infrastructure team builds the platforms, tooling, and services that power applied machine learning across Tinder. We provide the foundations for training, deploying, and monitoring large-scale ML systems that impact core experiences like Recommendations, Trust & Safety, Profile, Chat, Growth, and Revenue optimization
- In this position, we are looking for a Senior Machine Learning Infra Engineer who can build foundational ML infra, including feature store and efficient serving platform (LLM serving). Just to give you a high level overview of the team, ML team at Tinder is organized into three groups with different roles:
- Machine Learning Engineers who focus on modeling and algorithmic innovation
- Machine Learning Infrastructure Engineers (this role) who build the platforms and tools that enable scalable training, serving, and feature management
- Machine Learning Software Engineers who bridge the gap between research and production — delivering machine learning models into real-world Tinder features at scale
- In this role, you’ll partner closely with ML engineers, ML software engineers, and the CloudOps team to increase the ML organization’s overall velocity by building and evolving feature store infrastructure and enabling large-scale model serving.
- You’ll own projects end to end, working in tight alignment with ML teams to ensure infrastructure improvements are actually adopted and drive real impact.
- ML team at Tinder is driving significant business impact across domains and this infrastructure team is uniquely position to amplify that impact across the domains. For example, enabling more efficient and scalable model serving directly unlocks larger models across the domains, which can lead to consistent metric improvements across multiple product surfaces
- Build and evolve robust, scalable ML infrastructure that supports ML engineers across all Tinder business domains
- Set and drive the long-term technical direction for Tinder’s ML infrastructure
- Design, build, and operate production-grade ML serving infrastructure for ML models using Ray Serve and Triton
- Develop and maintain robust serving infrastructure specialized for serving large language models (LLMs) in-house
- Develop efficient ML serving platform using Ray Serve and Triton
- Build the foundation of Tinder’s feature store using Databricks and internal tooling
- Own infrastructure projects end to end—from design and implementation to adoption and measurable impact
- Partner closely with ML Engineers, ML Software Engineers, and CloudOps to ensure infrastructure directly enables better models and faster iteration
- Establish and propagate best practices in ML infrastructure, data engineering, and model serving
- Mentor and support junior engineers, raising the technical bar across the team
Our take
In today's society, online communication is rapidly replacing face-to-face interaction across various aspects of life, including professional, platonic, and even romantic relationships. Dating apps like Tinder, with their quick sign-ups and swipe-based interface, have revolutionized the way people connect.
Tinder's innovative approach has significantly reduced the social stigma associated with online dating. This, coupled with the global rise of smartphones, has created a strong tailwind for the app. However, Tinder faces new challenges from competitors like Hinge, Bumble, and Thursday, who all capitalize on similar "swipe-based" mechanics, potentially attracting users away from the platform.
To address this, Tinder is actively seeking ways to reinvent its core product. The company is exploring the development of "Tinderverse", a shared virtual reality experience. Additionally, it is testing "Tinder Coins", an in-app currency earned through positive user behavior, allowing access to premium features. These initiatives demonstrate Tinder's commitment to remaining at the forefront of the ever-evolving online dating landscape.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Company benefits
- Mind & Body: Take care of yourself with benefits to keep you physically and mentally healthy.
- Company Perks: As winners of Comparably’s 2022 Best Company Perks and Benefits Award, we’re proud to say we provide perks that make a difference
- Life @ Tinder: We support each other— from informal check-ins to snacks + catered lunches at HQ to the flexibility to take time off when you need it
Company HQ
Sunset Strip, West Hollywood, CA
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