Senior Machine Learning Engineer - Fan Insights & Guidance, S4X
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!We are looking for an experienced Machine Learning engineer who is passionate about building production ML systems impacting millions of Spotify fans. Our team is working on building ML models and foundational tech that will power many personalization experiences for fans interacting with their favorite artists on the Spotify platform. As a senior engineer in the team, you will not only coordinate and influence the direction within the team but also work with multiple stakeholders to power different personalization projects.
What you'll do
- Contribute to designing, building, evaluating, shipping, and refining Spotify’s personalization products by hands-on ML development
- Collaborate with a cross functional agile team spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and relevant ways
- Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users
- Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization
- Build upon Spotify’s ML infrastructure to deliver production-scale, end-to-end solutions
- Candidates are encouraged to pursue a t-shaped profile in DE or BE with a shared ownership inside the team
Who you are
- You are passionate about Machine Learning at scale in production
- You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with experience and expertise in personalized machine learning algorithms, especially recommender systems
- You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages. Experience with TensorFlow, PyTorch, Scikit-learn, XGBoost, etc is a strong plus
- You have experience with large-scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open-source API for it, Scio, and cloud platforms like GCP or AWS.
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation
- You understand how to translate product and business goals into tech
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 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.
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 APIs AWS Engineering GCP Machine Learning ML infrastructure ML models Python PyTorch Recommender systems Research Scala Scikit-learn Spark Streaming TensorFlow Testing XGBoost
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