Senior Machine Learning Engineer

TOGETHXR; San Francisco (CA); Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Flexible working model

Collaborative team culture

Inclusive environment

Job summary

TOGETHXR is seeking a Machine Learning Engineer to join its AI and Machine Learning team in San Francisco. You will develop ML models that enhance the athlete experience and ensure robust deployment of production systems.

The ideal candidate will have experience working with data pipelines, possess strong communication skills, and demonstrate innovation in product development. Strava offers a flexible hybrid work model, with significant collaboration across teams.

Qualifications

• Experience with building, shipping, and supporting ML models in production at scale.
• Proficient in exploratory data analysis and model prototyping.
• Strong interpersonal communication skills.

Responsibilities

• Drive key machine learning projects on the Strava platform.
• Innovate on models that improve athlete experience.
• Collaborate with cross-functional partners to deploy ML solutions.

Skills

Machine learning expertise

Strong communication skills

Data analysis

Python

Experience with ML tools (TensorFlow, PyTorch)

Backend services in cloud environments

Tools

Scikit-learn

Pandas

NumPy

Spark

Hadoop

SQL

Snowflake

Job description

We are looking for a Machine Learning 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.

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

What You’ll Do:

• 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: Drive 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 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 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

You Will Be Successful Here By:

• 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.

• Leading as an Owner: Owning your work end-to-end and being accountable for the outcomes in the projects you drive and landing impact for the business. Ensure the end-to-end system delivers as expected through collaboration with partners.

• 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.

• 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.

• Raising the ML standard: Help work towards best practices for model development, deployment, and maintenance.

• 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 numerous machine learning problems and broken them down into incremental tasks.

• Have demonstrated solid interpersonal and communication skills, and collaborative approach to drive business impact across teams.

• 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, and Sagemaker.

• Have built and worked on data pipelines using large scale data technologies (like Spark, Hadoop, EMR, SQL, and Snowflake).

• Are experienced and interested in production ML model operational excellence and best practices, like automated model retraining, performance monitoring, feature logging, and A/B testing.

• Have built backend production services on cloud environments like AWS, using languages like (but not limited to) Python, Ruby, Java, Scala, and Go.

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.

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