Machine Learning Engineer - NLP - Personalization
Engineering – Personalization
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Daily Mix to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.
The Personalization team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music and podcasts better than anyone else so that we can make great recommendations to every individual person and keep the world listening. Everyday, hundreds of millions of people all over the world use the products we build which include destinations like “Home” and “Search” as well as original playlists such as “Discover Weekly” and “Daily Mix.” We’re a team of technologists, product insight experts, designers, and product managers in Boston, New York, Stockholm, and London.
What you’ll learn and do:
- Collaborate with a cross functional agile team spanning user research, design, data science, product management, linguistics, and engineering to build out best practices in NLP pipelines
- Set up end-to-end model training, evaluation, and deployment pipelines utilizing Google Cloud Platform (GCP)
- Utilize cloud computing resources in the GCP ecosystem to maximize value and focus internal development efforts on differentiation
- Build or improve features that impact our partners and make them better utilizing ML solutions
- Develop privacy-preserving data sampling strategies to maximize the rate of improvement of our ML/NLP models
- Work with Product Insights and Data Curation teams to focus development efforts in ML to increase the quality of our Voice systems
- Develop individually to continue to grow your impact, and help mentor peers
- Help give hands-on technical leadership within the multidisciplinary team
- 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
- Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development
- Be part of an active group of machine learning practitioners in Boston (and across Spotify) collaborating with one another
Who you are:
- You have a strong background in machine learning, with experience and expertise in Natural Language Processing systems.
- You understand the data annotation pipeline from data selection to aligning labeling efforts to ML model improvements
- You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages. Experience with XGBoost, TensorFlow is also a plus.
- Strong background in Statistics and statistical inference techniques
- You preferably have experience with data pipeline tools like Apache Beam 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 are an expert at architecting data pipelines and are self-sufficient in getting the data you need to build and evaluate your models, using tools like Apache Beam or Spark.
- You have 2+ years of professional engineering experience working in a product-driven environment with technologies (Scala, Java, Python, or C++) and cloud platforms (GCP or AWS).
- You care about agile software development and a culture of constant learning and improvement
- You have experience and passion for mentoring and encouraging collaborative teams.
- You love your customers even more than your code
- We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music.
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 brilliant. 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 opportunity to enjoy and be inspired by 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 230 million users.