Remote Machine Learning Engineer - Music

Description:

• The Music Promotion team is building products that allow creators to promote their work to reach new audiences and create lasting connections with their fans.
• The company is looking for a Machine Learning Engineer to help build systems that accurately understand the performance of promotions, providing customers with actionable insights for their promotion strategies.
• As an ML Engineer, you will complete strategies for understanding the factors influencing the performance of promoted tracks globally.
• You will build data-driven solutions and effective online and offline strategies to efficiently iterate and evaluate model approaches.
• You will have access to a growing list of datasets, features, and ML infrastructure to continually experiment and improve the model-based approach.
• Responsibilities include contributing to the design, build, evaluation, shipping, and refinement of systems that enhance Spotify’s promotional performance through hands-on ML development.
• You will collaborate with a multidisciplinary team to optimize machine learning models for production use cases, ensuring efficiency, scalability, and adherence to success criteria.
• You will influence technical design, architecture, and infrastructure decisions to support diverse machine learning architectures.
• You will work with Data and ML Engineers to transition machine learning models from research and development into production.
• You will implement and monitor model success metrics, diagnose issues, and participate in an on-call schedule to maintain production stability.

Requirements:

• You must have experience implementing ML systems at scale in Java, Scala, Python, or similar languages, along with experience using ML frameworks such as TensorFlow or PyTorch.
• You should understand how to transition machine learning models from research to production and be comfortable with innovative architectures.
• A collaborative approach is essential, as you will work closely with research scientists, machine learning engineers, and data engineers to innovate and improve models.
• You must have experience optimizing machine learning models for production use cases.
• Preferably, you should have experience with data pipeline tools like Apache Beam, Scio, and cloud platforms like GCP.
• Exposure to causal ML models, including counterfactuals, is preferred.
• You should be familiar with crafting model success metric dashboards, diagnosing production issues, and be willing to participate in an on-call schedule to maintain performance.

Benefits:

• The United States base salary range for this position is $138,250 - $197,500 plus equity.
• Benefits include health insurance, six months of paid parental leave, and a 401(k) retirement plan.
• You will receive a monthly meal allowance and 23 paid days off.
• Additionally, there are 13 paid flexible holidays and paid sick leave.
• The salary range encompasses multiple levels, with leveling determined during the interview process based on relevant work history and interview performance.