WW is looking for candidates to help change people's lives. We are a global wellness technology company inspiring millions of people to adopt healthy habits for real life. We do this through engaging digital experiences, face-to-face workshops and sustainable programs that encourage people to move more, shift their mindset and eat healthier while enjoying the foods they love. By drawing on over five decades of experience and expertise in behavioral science, we build communities in order to deliver wellness for all.
Who we are
WeightWatchers is inherently a data product and we can leverage our data-a massive longitudinal dataset across a wealth of touch points and millions of members in different geographies and demographics-to create a profoundly personalized and impactful experience. The Data Science team is a separate entity from the analytics, data warehousing and data engineering teams, freeing us up for a singular focus: building awesome data products.
What you will do
The WW Data Science team is looking for a new senior member to help us build the infrastructure that powers our predictive models, recommenders, and data enrichment algorithms. In your role as a ML Ops Engineer you will help WW's Data Science team to develop, deploy, monitor, and maintain production machine learning (ML) models. You will build out and monitor CI/CD pipelines for automated image builds, running of tests, and deployment of models using e.g. GitHub Actions. You will be evaluating existing ML processes to identify areas of improvement, and will apply the latest open source technologies in the ML stack to enhance WW's predictive automation software.
Who you are
Along with production level software experience, you should demonstrate solid data science knowledge and understanding.

• Python is your jam! Along with python, you are strong in SQL.
• Machine learning product development experience, using state-of-the-art tooling
• Ability to create abstractions, APIs, and libraries
• Extensive knowledge of ML frameworks/libraries (e.g. scikit-learn, Pytorch, Tensorflow, transformers), data structures, data modeling, and software architecture within a cloud production environment
• Experience with Docker and Kubernetes

Base salary may vary depending on, but not limited to: skills, experience, and location.
Base Salary
$110,000/yr to $185,000/yr
#LI-Remote
At WW, it is our priority to cultivate a diverse and inclusive workplace. We are committed as individuals, as an organization, and as fellow humans, to advocate for and support our employees, our members, and our communities. We are proud to be an equal opportunity employer and we do not discriminate on the basis of sex, race, color, creed, national origin, marital status, age, religion, sexual orientation, gender identity, gender expression, veteran status, or disability.