About the Role

We believe that achieving personal goals starts with access to the right tools and data. Our platform empowers users to make informed choices and achieve their health, wellness, and fitness ambitions.

As a member of our team, you’ll contribute directly to improving the lives of millions of users by building predictive models and deploying AI solutions that enhance the platform experience. We foster a collaborative, mentorship-driven, and inclusive environment where innovation thrives.

Key Responsibilities

The Machine Learning Engineer will be instrumental in creating and deploying machine learning models that refine advertising strategies and enable smarter audience segmentation. You will develop scalable pipelines that support ad personalization, optimize targeting, and facilitate experimentation. This role involves close collaboration with stakeholders across marketing, product, and data teams, leveraging platforms like Google Ad Manager (GAM) to define and measure user cohorts.

Success requires a balance of technical skill, strategic thinking, and the ability to execute quickly while maintaining experimental rigor. Strong communication and collaboration will be essential for driving impactful outcomes.

What You’ll Do

• Design and deploy machine learning models and pipelines to enhance ad personalization, user segmentation, and audience analysis.

• Utilize ad tech tools such as GAM to define, implement, and evaluate user cohorts for targeting and experimental testing.

• Collaborate with cross-functional teams to establish success metrics and evaluate ML-driven marketing campaigns.

• Create frameworks for scalable testing and experimentation to improve advertising ROI.

• Drive end-to-end implementation of feature engineering, model training, and optimization pipelines for advertising use cases.

• Partner with stakeholders to identify and address opportunities for advanced targeting and improved campaign performance.

• Ensure models meet high standards of reliability, performance, and reproducibility in production environments.

What You Bring

• 4–6+ years of experience in machine learning, ideally in advertising, marketing tech, or user targeting domains.

• A Bachelor’s or Master’s degree in Computer Science, Statistics, Data Science, or a related field—or equivalent professional experience.

• Hands-on experience with ad tech platforms such as GAM, DV360, or similar tools.

• Expertise in Python and SQL, with a strong grasp of data preparation, model development, and experimentation techniques.

• A solid understanding of causal inference, attribution modeling, and A/B testing methodologies.

• A proven ability to collaborate across disciplines, communicate effectively with both technical and non-technical teams, and deliver impactful data solutions.

Preferred Skills

• Familiarity with cloud-based platforms and tools like AWS, Kubernetes, and Docker.

• Experience optimizing large-scale data pipelines and developing production-grade ML systems.

• A curiosity-driven approach to problem-solving, with a focus on leveraging data to innovate.

Our Mission

We are committed to creating a culture that values creativity, user-centric design, and continuous improvement. Join our team to make a tangible difference by empowering people with the insights and tools they need to achieve their goals.