Applied Machine Learning Engineer – Content Intelligence
|Published||December 14, 2022|
|Location||London (Remote), United Kingdom|
Delivering the best Spotify experience possible. To as many people as possible. In as many moments as possible. That’s what the Experience team is all about. We use our deep understanding of consumer expectations to enrich the lives of millions of our users all over the world, bringing the music and audio they love to the devices, apps and platforms they use every day. Know what our users want? Join us and help Spotify give it to them.
The Content Intelligence organization aims for Spotify to have the most complete and correct information in the music industry. Through a diverse set of initiatives including our content knowledge graph, human in the loop, creator/content representation, and violative content detection, our squads in Content Intelligence strive to accurately model the full landscape of content at Spotify.
We are looking for an Applied Machine Learning Engineer to join our Content Intelligence product area and help drive the direction and development of proactive content moderation at scale. As a part of our team, you will work closely with machine learning research as well as partner product and engineering teams to build, deploy and maintain in production ML models in the content understanding space. Your work will impact the experience of millions of users globally and be instrumental in keeping Spotify a safe and compliant platform where creativity can flourish.
What you'll do
- Contribute to designing, building, evaluating, shipping, and improving production ML services and methods through hands-on ML development in TensorFlow, Python, SQL, and Java.
- Perform data analysis to establish baselines and inform product decisions.
- Collaborate with a cross-functional agile team spanning research, data science, product management, and engineering to build new product features that improve the detection of content that violates Spotify’s Terms of Service.
- Thoughtfully communicate your work and experience in applied machine learning through both internal collaborations and mentorship opportunities.
- Use the Google Cloud Platform to train and deploy models at scale.
Who you are
- You have a strong background in applied machine learning and generalist content understanding, with experience and expertise in designing, building, and testing deep learning solutions.
- You are a technical and collaborative leader who can inspire and mentor others as well as receive mentorship and guidance yourself.
- You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
- You have demonstrated the ability to deliver results and make judicious tradeoffs between idealistic approaches and product impact.
- You have experience working with disparate data sources and sparse data, both structured and unstructured.
- You have previous industry experience with frameworks such as Tensorflow, Pytorch etc.
- You have experience with data pipeline tools such as Apache Beam, Scio, etc., and cloud platforms like GCP or AWS.
- You care about agile software processes, data-driven development, reliability, and responsible experimentation.
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 EMEA region in which we have a work location and is within working hours.
- Working hours? We operate within the Central European and GMT time zones for collaboration and ask that all be located in that time zone.
- 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.
Spotify is an equal opportunity employer. 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.