Senior Machine Learning Platform Engineer

San Francisco, CA

⚠️ We'll shut down after Aug 1st - try foo🦍 for all jobs in tech ⚠️

Strava

Strava connects millions of runners, cyclists, hikers, walkers and other active people through the sports they love – all on our mobile app and website.

View all jobs at Strava

Apply now Apply later

About This Role

Strava is the app for active people. With over 150 million athletes in more than 185 countries, Strava is where connection, motivation, and personal bests thrive. No matter your activity, gear, or goals, we help you find your crew, crush your milestones, and keep moving forward. Start your journey with Strava today.

Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward.

We are looking for a Senior Machine Learning Platform Engineer to join the growing AI and Machine Learning team at Strava. This team is responsible for sophisticated machine learning models and systems which provide value to Strava athletes including personalization, recommendations, search, and trust and safety. The team also maintains the ML platform and infrastructure that enables our team to iterate on models quickly and deploy them reliably at scale.

This is an important role on the team to develop and expand our machine learning platform. This lets us build models of higher quality with less friction. It helps ensure our models are served with stability and reliability, while ensuring we monitor model performance carefully. Ultimately you won’t just help with the things we are doing now, but also unlock our technological capabilities for the future.

We follow a flexible hybrid model that generally translates to half your time on-site in our San Francisco office— three days per week.

What You’ll Do:

  • Own scalable platform: Lead key projects to level up Strava’s ML tools and system in a way that grows with our use cases, model architectures, and athletes.
  • Build for a well-loved consumer product: Work at the intersection of AI and fitness to enable product experiences used by tens of millions of active people worldwide.
  • 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 across multiple surfaces and expand our technical ML capabilities.
  • Build from a rich dataset: Help us make use of Strava’s extensive unique fitness and geo datasets from millions of users to extract actionable insights, inform product decisions, and optimize existing features

You Will Be Successful Here By:

  • Holding empathy and perspective: Work closely with engineers and data scientists to understand the opportunities to help them succeed; they will be your customers!
  • Leading as an owner: Owning your work end-to-end and being accountable for the outcomes in the projects you lead, influencing the ML team, partner teams, and landing impact for the business. Ensure the end-to-end system delivers as expected through collaboration with partners.
  • Driving innovation with product in mind: Stay up-to-date with the latest research in machine learning, AI, and related fields. Experiment, advocate, and gain buy-in for innovative techniques to enhance our existing platform, resulting in step-function changes to how we build AI at Strava.
  • Raising the ML standard: Mentor engineers to shape how we do ML at Strava. Raise the standards for model development, deployment, and maintenance, and be a go-to source of knowledge of the field.
  • Collaborating in and across teams: Build relationships, advocate and communicate with cross-functional partners and product verticals to identify opportunities and bring your technical vision to life.
  • Being passionate about the work you are doing and contributing positively to Strava’s inclusive and collaborative team culture and values

What You’ll Bring to the Team:

  • Have worked on complex, ambiguous platform challenges and broken them down into manageable tasks with both strategies and tactical execution.
  • Demonstrated technical leadership in leading projects and the ability to mentor and grow early-career team members.
  • Have demonstrated strong interpersonal and communication skills, and a collaborative approach to drive business impact across teams.
  • Have worked with a variety of MLOps tools that fulfill different ML needs (like FastAPI, LitServe, Metaflow, MLflow, Kubeflow, Feast)
  • Are experienced in production ML model operational excellence and best practices, like automated model retraining, performance monitoring, feature logging, A/B testing
  • Have built backend production services on cloud environments like (but not limited to) AWS, using languages Python, Terraform, and other similar technologies.
  • Have built and worked on data pipelines using large scale data technologies (like Spark, SQL, Snowflake)
  • Have experience building, shipping, and supporting ML models in production at scale
  • Have 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

Compensation Overview:

At Strava, we know our employees are the most important ingredient to our success, and our compensation and total rewards programs reflect that. We take a market-based approach to pay, and pay may vary depending on the department and your location. Salary ranges are categorized into one of three tiers based on a cost of labor index for that geographic area. We will determine the candidate’s starting pay based on job-related skills, experience, qualifications, work location, and market conditions. We may modify these ranges in the future. For more information, please contact your talent partner.

Compensation: $180,000 - $210,000. This range reflects base compensation only and does not include equity or benefits. Your recruiter can share more details about the full compensation package, including the range specific to your location, during the hiring process.

For more information on benefits, please click here.

Why Join Us?

Movement brings us together. At Strava, we’re building the world’s largest community of active people, helping them stay motivated and achieve their goals.

Our global team is passionate about making movement fun, meaningful, and accessible to everyone. Whether you’re shaping the technology, growing our community, or driving innovation, your work at Strava makes an impact.

When you join Strava, you’re not just joining a company—you’re joining a movement. If you’re ready to bring your energy, ideas, and drive, let’s build something incredible together.

Strava builds software that makes the best part of our athletes’ days even better. Just as we’re deeply committed to unlocking their potential, we’re dedicated to providing a world-class, inclusive workplace where our employees can grow and thrive, too. We’re backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we’re expanding in order to exceed the needs of our growing community of global athletes. Our culture reflects our community. We are continuously striving to hire and engage teammates from all backgrounds, experiences and perspectives because we know we are a stronger team together.

Strava is 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.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

California Consumer Protection Act Applicant Notice

Apply now Apply later
Job stats:  0  0  0

Tags: A/B testing Architecture AWS Data analysis Data pipelines EDA FastAPI Kubeflow Machine Learning MLFlow ML models MLOps NumPy Pandas Pipelines Prototyping Python PyTorch R Research SageMaker Scikit-learn Snowflake Spark SQL TensorFlow Terraform Testing

Perks/benefits: Career development Equity / stock options

Region: North America
Country: United States

More jobs like this