What are the responsibilities and job description for the Machine Learning Engineer II - Subscriptions position at Spotify?
We in the Machine Learning product area in the Activation, Retention, Conversion studio are focused on building robust and scalable machine learning solutions that can personalize activation, retention and conversion funnels to improve important business metrics. Through an ensemble of machine learning models, we aim to provide the best suitable offer or non-credit card trial to demonstrate the value of Spotify Premium, with the ultimate goal of having direct impact on key business metrics like SUBS and MAU
Our vision is to build the machine learning models and infrastructure that offers a fully personalized and ML-optimized Offer as well as trial targeting with the intention of showing the right value to the right user at the right time
Our squad is a combination of Machine Learning Engineers, Data Engineers, Backend Engineers and Data Scientists. If this sounds like something you would be interested in working on, please apply.
\n- Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development
- Collaborate with a multi-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
- Help drive optimisation, testing, and tooling to improve quality
- Be part of an active group of machine learning practitioners in your mission and across Spotify
- You have a strong background in machine learning, theory, and practice.
- You are comfortable explaining the intuition and assumptions behind ML concepts, experience in the messaging space is a plus.
- You have hands-on experience implementing and maintaining production ML systems in Python, Scala and using libraries like Tensorflow or PyTorch.
- You are experienced with building data pipelines, and you are self-sufficient in getting the data you need to build and evaluate your models.
- You preferably have experience with cloud platforms like GCP or AWS.
- We offer you the flexibility to work where you work best! For this role, you can be within the EST time zone as long as we have a work location.
The United States base range for this position is $171,903 -$245,575 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. This range encompasses multiple levels. Leveling is determined during the interview process. Placement in a level depends on relevant work history and interview performance. These ranges may be modified in the future.
