Staff Machine Learning Engineer, Spotify
$187-267k
+ Equity; Salary is benchmarked on US rates and may vary by other locations
More information about location
Commercial music streaming service
Job no longer available
Commercial music streaming service
1001+ employees
Job no longer available
$187-267k
+ Equity; Salary is benchmarked on US rates and may vary by other locations
More information about location
1001+ employees
Company mission
To unlock the potential of human creativity—by giving a million creative artists the opportunity to live off their art and billions of fans the opportunity to enjoy and be inspired by it
Role
Who you are
- We are looking for a strong Staff Level MLE with experience in MLOps supporting Machine Learning systems at scale in production
- 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
What the job involves
- 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
- This role will be for a team focused on Text/NLP/LLMs
- You will be the technical lead for a small team of engineers building and maintaining text understanding tools for transcription, moderation, entity extraction and resolution, topic modeling, and summarization (to name a few)
- You will be responsible for crafting and delivering solutions involving Large Language Models, including training, fine-tuning, and maintaining these models
- You will team up with our Product and Engineering leadership to shape the future vision for text understanding tooling
- You will conduct thorough research and analysis of the latest industry trends in LLM developments and introduce groundbreaking use cases for internal use cases
- Collaborate with technical and non-technical business partners to develop analytics and metrics that describe the performance of our text understanding systems and the quality of our data
- Be a leading voice in an active community of machine learning practitioners across Spotify and leverage existing innovative tooling in the Spotify ecosystem. (TensorFlow, Kubeflow, DataFlow, python-beam, Google Cloud Platform)
- Contribute to our team-wide product ideation in collaboration with other specialists, researchers, product managers, and subject-matter experts on the team
Our take
Spotify was founded in an attempt to combat the rampant music piracy that was causing significant harm to the industry. The company has since taken music streaming mainstream and now has 180m+ paying subscribers across the world.
With features that include a highly accessible interface and a vast catalogue of artists, Spotify's strong brand has been able to maintain growth in spite of fierce competition from deep-pocketed rivals like Amazon and Apple. The company has achieved this by making smart acquisitions to move into other verticals to strengthen its offerings, especially podcasting, by acquiring Gimlet Media, Anchor and Parcast.
Spotify's future plans include rapid growth with a goal to become a one-stop destination for all digital sound, as well as AI and NFT integrations. However, high costs incurred from the acquisition of exclusive podcasts, increasing competitor strength, and weak bottom-line growth mean that the company must find a balance to maintain its position in the sector.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
23% employee growth in 12 months
Company
Funding (last 2 of 8 rounds)
Jan 2016
$1bn
CONVERTIBLE
Jun 2015
$526m
SERIES G
Total funding: $2.1bn
Company benefits
- Extensive learning opportunities, through our dedicated team, GreenHouse
- Flexible share incentives letting you choose how you share in our success
- Global parental leave, six months off - fully paid - for all new parents
- All The Feels, our employee assistance program and self-care hub
- Flexible public holidays, swap days off according to your values and beliefs
Company values
- Innovative: We move fast and take big risks
- Sincere: We have no time for internal politics
- Passionate: We revel in what we do
- Collaborative: We recognise that we're all in this together
- Playful: We don't take ourselves too seriously
Company HQ
Norrmalm, Stockholm, Stockholms län
Articles
Leadership
Daniel Ek
(CEO & Chairman)Founded Spotify in 2006. Previously worked as an executive at Tradera, an auction company that was sold to eBay and was briefly the CEO of uTorrent.
People progressing
Joined as a Conversion Manager in the Growth Team. Promoted three times over seven years to Senior Director - Head of Growth.
Joined as a Customer Advisor. Since then has had the role titles Senior Advisor, Content Associate, Team Coach, and Operations Manager - Primary Support. Hurst is now currently the Business Operations Manager of Music.
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