MyFitnessPal is seeking a Staff Machine Learning Engineer to lead the technical implementation of cutting-edge AI products and machine learning platforms. This role combines hands-on technical leadership with strong mentorship expectations, focusing on building and scaling recommendation systems and search features that impact millions of daily users.
The position sits within MyFitnessPal's Data Science team, where you'll work on creating predictive models and AI that drives the MyFitnessPal ecosystem. The team values collaboration, mentorship, and inclusive environments, using technologies like MySQL, Snowflake, Databricks, Elasticsearch, Python, SQL, Kubernetes, Docker, Scale.ai, AWS Ground Truth, and Doccano.
As a Staff Machine Learning Engineer, you'll be responsible for designing and maintaining robust, production-grade ML models and MLOps systems that power personalized experiences across the platform. You'll lead the development of recommendation models and AI features while partnering with product engineering, data engineering, and data operations teams to ensure best practices in all aspects of development and deployment.
The role requires 7+ years of machine learning experience in production settings, with deep expertise in recommendation systems, search, NLP, LLMs, and deep learning. You should have a proven track record of building centralized machine learning platforms and experience leading data science teams to deliver measurable product value.
MyFitnessPal offers a competitive compensation package ranging from $170,000 to $215,000, along with comprehensive benefits including healthcare, parental planning, mental health benefits, annual performance bonus, and 401(k) with match. The company promotes a flexible work environment with their Responsible Time Off policy and various wellness initiatives, including monthly wellness allowances and dedicated mental health days.
The company culture emphasizes personal connections, work-life balance, and professional growth through mentorship programs and learning opportunities. They're committed to diversity and inclusion, encouraging applications from candidates with various backgrounds and experiences, even if they don't meet 100% of the qualifications.