Machine Learning Engineer - Music Promotion (NY)

Avenue Code is building products for creators to promote their work and connect with fans. They are seeking a Machine Learning Engineer to develop systems that provide insights into promotion performance and help optimize strategies for various customers.

Responsibilities:

• Contribute to the design, build, evaluation, shipping, and refinement of systems that improve Spotify’s promotional performance with hands-on ML development
• Collaborate with a multidisciplinary team to optimize machine learning models for production use cases, ensuring they are highly efficient, scalable, and consistently meet well-defined success criteria
• Influence the technical design, architecture, and infrastructure decisions to support new and diverse machine learning architectures
• Work with Data and ML Engineers to support transitioning machine learning models from research and development into production
• Implement and monitor model success metrics, diagnose issues, and contribute to an on-call schedule to maintain production stability

Requirements:

• You have experience implementing ML systems at scale in Java, Scala, Python or similar languages as well as experience with ML frameworks such as TensorFlow, PyTorch, etc
• You have an understanding of how to bring machine learning models from research to production and are comfortable working with innovative, cutting-edge architectures
• You have a collaborative mindset, enjoy working closely with research scientists, machine learning engineers, and data engineers to innovate and improve models
• You have experience in optimizing machine learning models for production use cases
• You preferably have experience with data pipeline tools like Apache Beam, Scio, and cloud platforms like GCP
• You have some exposure to causal ML models, including things like counterfactuals
• You are familiar with creating model success metric dashboards, diagnosing production issues, and are willing to take part in an on-call schedule to maintain performance