Senior Machine Learning Engineer - Finance (Remote Eligible - Americas)
New York, NY /
Engineering – FinE /
Our team helps Spotify make strategic decisions using machine learning and using our petabytes of data. From understanding and forecasting how podcasts are evolving on our platform, to modeling user behavior and how people like to consume music and podcasts. We work with teams across the company to model and quantify what happens on our platform and build ML products that help them make better and data driven decisions.
Our team is seeking a motivated and self driven ML practitioner to help us build, productionize and manage our internal ML product and set best practices for continued evolution and support of them.
What you'll do
- Contribute to designing, building, evaluating, shipping, and refining our tools by hands-on ML development.
- Collaborate with a cross functional agile team spanning data scientist, data engineering, product management, and business experts to build new product features that advance our mission to understand our platform and help us sustainably grow as a business.
- Prototype new approaches and production-ize solutions at scale for our hundreds of millions of active users.
- Help drive optimization, testing, and tooling to improve quality.
- Be part of an active group of machine learning practitioners in New York.
- Mentor more junior members of the team on mathematical modeling and ML best practices.
Who you are
- You have a strong background in machine learning, mathematical modeling and statistics.
- You have hands-on experience implementing production machine learning systems at scale in Python, or similar languages. Experience with XGBoost, TensorFlow or PyTorch is also a plus.
- You preferably have experience with data pipeline tools such as Google Dataflow, Apache Beam/Scio, Spark or Flink, and cloud platforms like GCP or AWS. Experience with distributed systems is a plus.
- You are comfortable writing SQL queries, exploring data, and developing good hypotheses for product improvements
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation.
- Be an active contributor and technical leader to machine learning practitioners within AIR and Spotify.
- You like to operate at the cutting edge of ML technology and welcome challenging problems.
Where you'll be
- We are a distributed workforce enabling our band members to find a work mode that is best for them!
- Where in the world? For this role, it can be within the Americas region 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? We operate within the Eastern Standard time zone for collaboration
You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
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 345 million users.