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The Hendrix ML Platform team is dedicated to developing a robust, Spotify-wide platform for training and serving machine learning models. This platform streamlines the productionization of AI and ML models by mitigating the incidental complexities involved in creating backend services for serving predictions and training models.
What You'll Do
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
Spotify transformed music listening forever when we launched in 2008. Our mission is 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 chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
What You'll Do
- Contribute to Spotify ML Platform SDK and build tools for various ML operations.
- Collaborate with Machine Learning Engineers (MLE), researchers, and various product teams to deliver scalable ML platform tooling solutions that meet the timelines and specifications of given requirements.
- Work independently and collaboratively on squad projects that often requires learning and applying new technologies that may go beyond existing skillsets.
- Manage and maintain large scale production Kubernetes clusters for ML workloads, including ML platform infrastructure and necessary dev ops.
- Designs, documents and implements reliable, testable and maintainable solutions ML infrastructure capabilities.
- You have 3+ years of hands-on experience productionize ML models either by collaborating with Knowledge of deep learning fundamentals, algorithms, and open-source tools such as Huggingface, Ray, PyTorch or TensorFlowGood to have an understanding of distributed training leveraging GPUs and Kubernetes
- You have a general understanding of data processing for ML
- You have experience with agile software processes and modular code design following industry standards
- You have hands-on experience implementing and maintaining production ML systems in Python, Scala, or similar languages
- This role is based in Toronto, Canada
- We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
Spotify transformed music listening forever when we launched in 2008. Our mission is 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 chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
Key Skills
Ranked by relevance
machine learning
deep learning
kubernetes
pytorch
python
scala
ai
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- Posted
- Aug 12, 2025
- Type
- Full-time
- Level
- Entry
- Location
- Toronto
- Company
- Spotify
Industries
Musicians
Categories
Engineering
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3 roles aligned with this opportunity
View Job Details
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Staff Machine Learning Engineer
2026-05-14
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Not Applicable
Sweden
Musicians
Engineering
View Job Details
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Machine Learning Engineer
2026-05-14
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Senior Machine Learning Engineer - Messaging Platform
2026-05-11
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