Machine Learning Engineer - Audio Understanding
New York City
Applications have closed
Spotify
We grow and develop and make wonderful things happen together every day. It doesn't matter who you are, where you come from, what you look like, or what music you love. Join the band!What you'll do
- Tackle data-related problems involving some of the most diverse datasets available, using your experience to follow best practices in ML and data engineering.
- Work in an agile team spanning software engineers, research scientists, and product managers to productionize ML research at scale for hundreds of millions of active users.
- Build best-in-class infrastructure and tooling to accelerate our research-to-product efforts and to enable efficient cloud-based deployment and testing of audio processing models.
- Work with researchers and other ML engineers to debug and optimize ML models, supporting inference (and training) tasks at high scale.
- Collaborate with customer teams to deploy our research in products around Spotify, in backend, data, mobile, core, and other code bases.
- Scope the feasibility of projects through quick prototyping with respect to performance, quality, time and cost.
Who you are
- You have professional experience working with Machine Learning and Python for product applications.
- You can architect distributed data pipelines to build and evaluate models, using tools like Apache Beam or Spark.
- You have previous experience debugging, profiling, optimizing, or deploying TensorFlow models at scale.
- You have worked with cloud platforms like GCP / AWS / Azure.
- You have proven experience implementing and maintaining large-scale production software systems.
- You are interested in learning more about audio processing and music information retrieval and you're excited about building products that use such technologies.
- BENEFICIAL: You have experience with deep learning techniques for content based processing (audio, image, video data).
Where you'll be
- We are a distributed workforce enabling our band members to find a work mode best for them!
- Where in the world? For this role, it can be within the US east coast region or across Europe in which we have a work location
- Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our work from anywhere options here
- Working hours? Our team is distributed between Central Europe and NYC, and we collaborate in the morning (Eastern Standard Time) / afternoon (Central European Time).
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service with a community of more than 381 million users.
Global COVID and Vaccination DisclosureSpotify is committed to safety and well-being of our employees, vendors and clients. We are following regional guidelines mandating vaccination and testing requirements, including those requiring vaccinations and testing for in-person roles and event attendance. For the US, we have mandated that all employees and contractors be fully vaccinated in order to work in our offices and externally with any third-parties. For all other locations, we strongly encourage our employees to get vaccinated and also follow local COVID and safety protocols.
This role is not eligible for hire in Colorado, USA.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile AWS Azure Data pipelines Deep Learning Engineering GCP Machine Learning ML models Pipelines Prototyping Python Research Spark Streaming TensorFlow Testing
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