Software Engineer, Machine Learning Infrastructure - Peloton Interactive｜Meet.jobs

ABOUT THE ROLE

The AI/ML organization works on ML-powered consumer products that incorporate computer vision and recommender systems into the fitness domain. We are looking for a software engineer to drive ML infrastructure and operations for the AI/ML teams. Their main focus will be to work closely with ML Engineers, data engineers, software engineers and data analysts to help support the future of machine learning development in connected fitness. The engineer will build the connective tissue between the data, infrastructure teams and machine learning engineers focusing on vital tools and infrastructure to support model development & deployment pipelines, CI / CD, testing and offline experimentation at scale. This is a unique opportunity in the industry for someone to work on data, infrastructure and tooling that could potentially support multiple ML teams within Peloton.

YOUR DAILY IMPACT AT PELOTON

• Build, evolve, and scale state-of-the-art machine learning system infrastructure powering Peloton’s connected fitness data.
• Work with other machine learning engineers, researchers and backend engineers to implement scalable infrastructure solutions for ML model development, model lifecycle management, model monitoring and offline experimentation.
• Work on building an internal training platform that accelerates the velocity of offline experimentation for ML engineers.
• Collaborate with other ML engineers and data engineers to design, build and deploy data stores that support batch pipelines as well as real-time recommendations.

YOU BRING TO PELOTON

• 2+ Years of experience in MLOps developing infrastructure and platforms to power Machine Learning at scale.
• Strong programming background, with extensive experience preferably in Python.
• Experience with multiple technologies from the following list: Spark, Pandas, AWS, MLFlow, Airflow, PyTorch, Jupyter, Kubernetes, MySQL & NoSQL databases.
• Innovative, biased towards action in fast-paced environments.
• Able to take complete ownership of a feature or project.
• Bonus: Experience setting up ML CI / CD pipelines, testing and validating code and components, testing and validating data, data schemas, and models.
• Bonus: Experience working with large datasets with distributed data processing frameworks like Spark.
• Bonus: Experience building an internal training platform that supports multiple ML engineers with their offline experimentation.

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Peloton Interactive focuses on Hardware, Retail, Fitness, Video Streaming, and Android. Their company has offices in New York City. They have a very large team that's between 1001-5000 employees. To date, Peloton Interactive has raised $1.041B of funding; their latest round was closed on August 2018 at a valuation of $4.125B.

You can view their website at http://www.onepeloton.com or find them on Twitter, Facebook, and LinkedIn.