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AI Systems Engineer(m/w/x)
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
- English – Fluent
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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AI Systems Engineer(m/w/x)
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
- English – Fluent
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
About the Company
Huawei Research Center Germany
Industry
IT
Description
Huawei is a leading global ICT solutions provider advancing innovation in information and communications technology.
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- Huawei Research Center Germany & Austria
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