NLP Research Engineer - 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. Every day, 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.
The Spotify Personalization Voice team is looking for an NLP Research Engineer to join our team. We are seeking a candidate with strong ML fundamentals, extensive experience in Human Language Technologies, and strong analytical skills, to help us develop NLP components for integration across a number of devices and customer experiences.
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 NLP systems at the core of the Spotify experience
- Build or improve features that impact our partners and make them better utilizing our NLU/NLP solutions
- Develop privacy-preserving data sampling strategies to maximize the rate of improvement of our ML/NLP models
- Design and implement data selection and annotation pipelines that maximize targeted improvement of existing NLP systems.
- Help give hands-on leadership around NLP solutions within the multidisciplinary team
- Set up end-to-end model training, evaluation, and deployment pipelines utilizing Google Cloud Platform (GCP)
- Be part of an active group of ML and NLP practitioners in Boston (and across Spotify) collaborating with one another
- Develop individually to continue to grow your impact, and help mentor peers
Who you are:
- You have a PhD in Computational Linguistics, Machine Learning, or related area
- You possess solid hands-on skills in sourcing, cleaning, manipulating, analyzing, visualizing, and modelling of real data
- You have hands-on experience implementing production NLP 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 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.
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.