Staff Machine Learning Engineer

5 days ago

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Spotify

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5001 - 10000

Description

• Delivering the best Spotify experience possible, to as many people as possible, in as many moments as possible. • 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. • As a Staff Machine Learning Engineer in our Content Understanding teams, you will help define and build ML deployed at scale in support of a broad range of use cases driving value in media and catalog understanding. • We are looking for a strong Staff Level MLE with experience in MLOps supporting Machine Learning systems at scale in production.

Requirements

• Both academic and proven experience in text understanding and natural language processing solutions, such as Large Language Models (LLMs) and Speech-to-Text transcription • Expertise with training, fine-tuning, deploying, and maintaining LLMs, including experience working with popular third-party foundation models, such as Llama, OpenAI, and Gemini • Familiarity with various fine-tuning techniques in the LLM domain, such as RAG and LoRA adapters • Extensive experience working in a product and data-driven environment (Python, Scala, Java, SQL, or C++, with Python experience required) and cloud platforms (GCP or AWS). • Understand storage solutions and when to use them (e.g. Graph Database, Cassandra, Relational database). • You have experience architecting data pipelines and are self-sufficient in getting the data you need to build and evaluate models, using tools like Dataflow, Apache Beam, or Spark. • You have a good understanding of MLOps and the model lifecycle (AB/Testing, experimentation, push and maintaining models in production, observability, and monitoring) • You’re familiar with the industry trends and keep up with the latest product offerings, and can understand trade-offs of existing solutions. • You have excellent communication skills and the ability to translate business intuition into data-driven hypotheses that result in impactful engineering solutions. • You love your customers even more than your code. • You have experience and passion for mentoring and encouraging collaborative teams. • You have experience in cultivating a strong engineering culture in an agile environment.

Benefits

• Health insurance • Six month paid parental leave • 401(K) retirement plan • 23 paid days off • 13 paid flexible holidays • Paid sick leave