Strava is looking for a Senior Machine Learning Engineer to join their AI and Machine Learning team to design, roadmap, and implement innovative machine learning algorithms and improve the systems and tools behind the ML pipeline.
Requirements
- Experience building, shipping, and supporting ML models in production at scale
- Experience with exploratory data analysis and model prototyping, using languages such as Python or R and tools like Scikit learn, Pandas, Numpy, Pytorch, Tensorflow, Sagemaker
- Experience building and working on data pipelines using large scale data technologies (like Spark, Hadoop, EMR, SQL, Snowflake)
- Experience with production ML model operational excellence and best practices, like automated model retraining, performance monitoring, feature logging, A/B testing
- Experience building backend production services on cloud environments like AWS, using languages like (but not limited to) Python, Ruby, Java, Scala, Go
- Have worked on complex, ambiguous machine learning problems and broken them down into manageable tasks with both strategies and tactical execution.
- Have demonstrated technical leadership in leading projects and the ability to mentor and grow early career team members.
Responsibilities
- Build for a Well Loved Consumer Product: Work at the intersection of AI and fitness to launch and optimize product experiences that will be used by tens of millions of active people worldwide
- Own End to End AI Systems: Lead key projects powered by ML on the Strava platform end-to-end, from initial model prototyping to shipping production code to scaling and optimizing inference and deployment
- Shape AI at Strava: Be a strong voice and mentor on a highly collaborative team with a range of experience levels. Work across teams to deploy ML solutions in multiple surfaces and build out our technical ML capabilities.
- Innovate in AI for Fitness: Design and develop novel models and methodologies to take on novel problems in that improve athlete experience, including recommendation systems, activity prediction, and personalized insights
- Build from a rich dataset: Explore and use Strava’s extensive unique fitness and geo datasets from millions of users to extract actionable insights, inform product decisions, and optimize existing features
- Driving innovation with Product in mind: Stay up-to-date with the latest research in machine learning, AI, and related fields. Experiment, advocate and get buy-in for innovative techniques to improve existing products or explore new features that result in step function changes to how we build AI at Strava.
- Analyzing the Data: Work closely with product managers, data scientists, and engineers to find opportunities for applying machine learning to drive business impact and enhance Strava’s features and measure impact.
Other
- Have demonstrated strong interpersonal and communication skills, and collaborative approach to drive business impact across teams.
- Be passionate about the work you are doing and contributing positively to Strava’s inclusive and collaborative team culture and values
- We follow a flexible hybrid model that generally translates to around half your time on-site in our San Francisco Office—roughly three days per week.
- We are an equal opportunity employer. In keeping with the values of Strava, we make all employment decisions including hiring, evaluation, termination, promotional and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight.
