Senior Machine Learning Engineer @ Spotify
placeToronto, ON
attach_money CA$150,000
businessOn Site
scheduleFull Time
Posted 1 day ago
Your Application Journey
Interview
Email Hiring Manager
***** @spotify.com
Recommended after applying
Job Details
About the Role
The Senior Machine Learning Engineer position on the Hendrix ML Platform team at Spotify is focused on developing a robust, Spotify-wide AI/ML platform for training and serving machine learning models. This platform streamlines the productionization of models and simplifies backend service creation for serving predictions.
What You'll Do
- Contribute to the Spotify ML Platform SDK and build tools for ML operations.
- Collaborate with ML Engineers, researchers, and product teams.
- Work independently and in squads to learn and apply new technologies.
- Manage large-scale production Kubernetes clusters for ML workloads.
- Design, document, and implement reliable ML infrastructure solutions.
Who You Are
- 6+ years of hands-on experience in production ML infrastructure using Python, Go, or similar.
- Knowledgeable in deep learning, algorithms, and open-source tools such as Huggingface, Ray, PyTorch, or TensorFlow.
- Experienced with distributed training and Kubernetes management.
- Familiar with data processing for ML and agile software development.
Where You'll Be
This role is based in Toronto, Canada with a flexible work arrangement that allows remote work with occasional in-person meetings.
Key skills/competency
- Machine Learning
- Python
- Go
- Kubernetes
- TensorFlow
- PyTorch
- Huggingface
- DevOps
- Distributed Training
- Agile
How to Get Hired at Spotify
🎯 Tips for Getting Hired
- Customize your resume: Highlight ML platform and Kubernetes experience.
- Research Spotify: Understand their AI/ML initiatives and culture.
- Showcase projects: Present scalable ML infrastructure achievements.
- Practice technical interviews: Focus on Python, Go, and Kubernetes questions.
📝 Interview Preparation Advice
Technical Preparation
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Review Python and Go code examples.
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Practice Kubernetes cluster management tasks.
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Study ML frameworks and distributed training.
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Revisit production ML deployment case studies.
Behavioral Questions
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Describe project collaboration experiences.
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Explain problem-solving under pressure.
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Discuss adapting to new technologies.
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Share teamwork and feedback examples.
Frequently Asked Questions
What technical skills are essential for a Senior Machine Learning Engineer at Spotify?
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How does Spotify support continuous learning for the Senior Machine Learning Engineer role?
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What are the work arrangements for the Senior Machine Learning Engineer spot at Spotify?
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