At Playlist, life's richest moments happen when people step away from screens to move, connect, explore, and play. We're building the definitive platform for intentional living, connecting people with inspiring experiences in fitness, wellness, and beyond. With popular brands like Mindbody and ClassPass, Playlist empowers businesses and individuals, making it effortless for aspirations to become actions. Join us in reshaping technology's role to foster meaningful, real-world connections.

ClassPass offers thousands of fitness and wellness experiences worldwide, helping people lead active, balanced lifestyles. Our platform makes discovering and enjoying activities simple, personalized, and joyful—whether it's fitness classes, self-care sessions, a healthy lunch, or a new adventure. Join us in shaping healthier, more vibrant communities around the globe.

Who we are

We're a passionate engineering, platform, and operations team, developing and supporting ground-breaking products. Together, we'll build for the future, creating more opportunities for wellness businesses around the world to help their customers lead full, healthy lives. We push ourselves and our company to always strive for this higher purpose, recognizing the power in working together toward the same goal. We believe in building a diverse company where everyone feels safe bringing their authentic selves to work. And we believe that the secret to success is our people. Join the team, and let's see what we can accomplish together!

About the team

The ClassPass ML & Data team builds the models and data systems that power core parts of the member and partner experience, including pricing, personalization, search, and inventory. We work closely with data scientists, product managers, and engineering teams across the company, and we value engineers who bring their own ideas and see them through to measurable impact. We're growing the team and looking for an engineer who loves turning data into real business results.

You'll likely spend time working on

Owning features end to end: discovery, analysis, defining success metrics, building, launching, and measuring impact
Designing, building, and modernizing data models and ETL pipelines in dbt and Snowflake
Building, deploying, and monitoring ML models in production for problems like recommendations, personalization, pricing, and marketplace density
Testing hypotheses quickly, with data and statistical rigor
Writing technical design documents (TDDs) and partnering with engineers, data scientists, and product managers to shape solutions
Applying backend engineering best practices: testing, CI/CD, code reviews, and reliable deployments
Leading cross-functional projects and sharing knowledge across teams

You'll thrive in this role with experience in

5+ years in software, data, or ML engineering (or similar), including shipping and maintaining ML models in production
Strong hands-on experience with dbt and Snowflake (or comparable modern data-warehouse tooling at scale)
Proficiency in SQL and Python
Solid grounding in statistics and experimentation: choosing the right model and understanding the tradeoffs
Backend engineering fundamentals: CI/CD, testing, deployment, and observability
A track record of connecting technical work to business outcomes, and the ability to explain it clearly in writing and in conversation
Comfort with ambiguity, a bias for action, and a collaborative, feedback-friendly approach

Nice to have

Recommender systems, search and ranking, or pricing and optimization experience
Marketplace or location-aware modeling
Workflow orchestration and ML tooling (e.g., Airflow, SageMaker, MLflow)

It is Playlist’s intent to pay all Team Members competitive wages and salaries that are motivational, fair and equitable. The goal of Playlist’s compensation program is to be transparent, attract potential employees, meet the needs of all current employees, and encourage Team Members to stay with our organization. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location.