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HUHuawei Research Center Germany

AI Systems Engineer(m/w/x)

Dresden, München
Full-timeOn-site
AI/ML

Optimizing ML models for mobile hardware, balancing power, latency, and accuracy. Machine learning engineering foundations and mobile AI deployment experience required. Healthy meals in company canteen, language courses.

Requirements

  • BSc/Master or PhD in Computer Science or related disciplines
  • Machine learning engineering foundations
  • ML model evaluation
  • ML inference pipeline integration
  • Mobile AI deployment experience
  • Low-level performance tuning
  • ARM architecture familiarity
  • Mobile GPU/NPU familiarity
  • Efficient hardware acceleration use
  • Experimentation and benchmarking
  • Profiling tools usage
  • A/B testing experience
  • On-device performance monitoring
  • Model optimization techniques
  • Excitement to learn model optimization
  • Fluent English (written and spoken)

Tasks

  • Optimize machine learning models for mobile and resource-constrained platforms
  • Enable fast, reliable, and privacy-preserving user experiences
  • Engineer performance-critical systems balancing power, latency, and accuracy
  • Target various hardware including ARM CPUs, mobile GPUs, and NPUs
  • Collaborate with AI and Systems engineers
  • Translate model architectures into production-ready implementations
  • Build robust deployment pipelines using TensorFlow Lite or custom runtimes
  • Ensure scalable delivery and monitoring of edge AI workloads
  • Design solutions reducing cloud dependency
  • Improve responsiveness of edge AI
  • Enhance user data privacy with edge-first intelligence

Education

  • Bachelor's degree

Languages

  • EnglishFluent

Tools & Technologies

  • ARM architecture
  • mobile GPUs
  • NPUs

Benefits

Free or Subsidized Food

  • Healthy meals in company canteen

Learning & Development

  • Training opportunities
  • Language courses (German, Mandarin)

Informal Culture

  • Diverse and welcoming environment
  • Motivated team

Purpose-Driven Work

  • Self-responsible work
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