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SeniorFull-timePythonPyTorchCI/CDAIML
Salary Range
$132,600 - $179,400 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Backend Engineer to join Spotify’s Personalization team. This role focuses on building and operating backend services that power Spotify’s voice experiences, including text-to-speech (TTS) and speech recognition (ASR) capabilities.
Key Responsibilities
- →Design, build, and operate backend services and platforms that power Spotify’s voice experiences.
- →Own production systems end-to-end, from APIs and service orchestration to data flows, observability, and reliability.
- →Partner closely with ML and research engineers to productionize models and improve system interfaces.
- →Drive technical design for new capabilities and infrastructure, making trade-offs across latency, cost, performance, and reliability.
- →Champion engineering excellence across code quality, testing, CI/CD, monitoring, incident management, and documentation.
- →Collaborate with product, design, and insights to turn ambiguous problem spaces into clear technical roadmaps.
- →Contribute to broader architecture so services integrate with evolving agentic experiences.
- →Mentor engineers and share best practices across the team.
Requirements
- ✓Experience building and operating large-scale, distributed backend services in modern stacks.
- ✓Comfortable working in Python and improving production codebases.
- ✓Ownership of systems end-to-end: design, implementation, deployment, on-call, and iterative reliability improvements.
- ✓Ability to collaborate across disciplines and create clean interfaces that help teams move faster.
- ✓Ability to reason clearly about trade-offs and communicate decisions effectively.
- ✓Technical leadership in ambiguous spaces—shaping designs, aligning stakeholders, and driving delivery.
- ✓Strong product mindset and user impact focus, using data and feedback to iterate.
- ✓Experience with speech, audio, or ML-adjacent systems (TTS/ASR, model serving platforms, PyTorch/CUDA, low-latency serving) is a plus.
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