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Sr Software Engineer - Machine Learning & Data

  • United States

The base salary range for this position in the United States is $150,000 to $200,000.

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Job details

Pay
The base salary range for this position in the United States is $150,000 to $200,000.
Posting language
English
Posted

Original job description

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. The base salary range for this position in the United States is $150,000 to $200,000. The total compensation package for this position may also include a performance bonus, benefits and/or other applicable incentive compensation plans. Have we piqued your curiosity?

Sound like the role for you? We’d love to hear from you! Even if you’re not 100% sure about potential fit, we still encourage you to apply. We’re looking for the right person, not the perfect series of checkboxes.

The Company is an Equal Opportunity Employer. We highly value diversity at our company and encourage people of all different backgrounds, experiences, abilities and perspectives to apply. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other protected characteristics.

By entering your email and phone number and submitting your application, you consent to receive emails, calls and SMS about your application and other roles at The Company, including by auto-dialer. Message and data rates may apply. Opt-out or text STOP to cancel at any time. If you are a California resident or reside outside the United States then by submitting your application you confirm that you have read, understood, agree and - where applicable - grant your prior, free, informed and express consent for the processing of your personal information, including sensitive personal information, as described in our California Applicant Privacy Notice or International Applicant Privacy Notice (as applicable).

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