Spotify is looking for an extraordinary Lead ML Engineer to join our team. You will help give leadership to a cross-functional group innovating Spotify’s natural language capabilities (e.g., NLU, NLG, Information Extraction, Parsing, ASR, TTS) and serve as a go-to authority in this area company-wide. Above all, your work will impact the way the world experiences music.
What you’ll do
- Significantly contribute to designing, building, evaluating, shipping and refining Spotify’s natural language capabilities, especially by high-capacity hands-on development
- Actively collaborate with software engineers, data scientists, data engineers, ML engineers, researchers, designers, and product managers to get things done
- Significantly influence and exemplify how teams work together to delivering natural language capabilities in an agile environment as well as identifying and articulating the business goals motivating them
- Facilitate natural language technology excellence across the company through information sharing, consultations, and other avenues you identify
- Mentor other engineers in growing both their technical and collaborative skills
- Be an influential member of an active group of machine learners in Boston and across Spotify learning from and encouraging one another
- Work from our Boston office (Davis Square), with frequent collaboration with and occasional travel to our other offices (e.g., Stockholm, New York)
Who you are
- Graduate-level expertise (e.g., Ph.D.) in computer science or a related field with a focus natural language technology, especially machine learning based approaches
- 7+ years of industrial experience in developing natural language products
- Hands-on experience implementing systems at scale in Java, Scala, Python or similar languages
- You have demonstrated thoughtful and energetic support for agile software processes, healthy teams, data-driven development, reliability, and disciplined experimentation
- You preferably have experience with architectures using distributed data processing and storage frameworks like Spark, Scio, Google BigQuery, and Cassandra, etc.
We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music.