Hybrid Engineering Manager – Machine Learning

Posted 3 weeks ago

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About the role

  • Own the technical roadmap and model strategy for generative music, including diffusion and transformer-based approaches
  • Lead the full lifecycle from research to production, championing training, evaluation, and deployment for real-time inference
  • Drive the productionisation of inference through model optimisation (distillation, quantisation), caching, and cost controls
  • Build and maintain team health through effective rituals, 1:1s, and fostering a psychologically safe, high-ownership culture
  • Manage cross-team dependencies and delivery with data, MLOps, and product engineering teams

Requirements

  • Deep ML engineering background with hands-on experience in generative diffusion models for audio/music (including PyTorch and modern training stacks)
  • Proven experience deploying ML systems into production at scale, with a focus on latency, stability, and cost
  • Strong ML system design and architecture skills across the full machine learning lifecycle
  • Track record of managing engineering teams
  • Demonstrated ability to set clear goals, manage performance, and grow engineers through mentorship and feedback

Benefits

  • Equal opportunity employer
  • Health workplace
  • Professional development

Job title

Engineering Manager – Machine Learning

Job type

Experience level

Mid levelSenior

Salary

Not specified

Degree requirement

Bachelor's Degree

Tech skills

Location requirements

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