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NONomitri

Machine Learning Engineer for Edge AI(m/w/x)

Berlin
Full-timeWith Home OfficeExperienced
AI/ML

Deploying computer vision solutions for retail environments using PyTorch and ONNX Runtime. Deep learning for computer vision expertise required. Flexible hybrid work, international team.

Requirements

  • Software engineering (Python)
  • Deep learning for Computer Vision
  • PyTorch
  • Model deployment and optimization with ONNX Runtime and TensorRT
  • Parameter / model studies, managing experiments
  • SQL, Git, Linux
  • Computer Vision
  • Understanding and implementing research papers
  • Efficient Deep Learning / Model Compression / Knowledge Distillation
  • Data & annotation management
  • Model performance optimization for NVIDIA hardware platforms
  • Generative Models for text, image and video
  • TensorRT / ONNX & ONNX Runtime
  • CI / CD
  • Docker / Containers
  • Cloud storage and computer

Tasks

  • Contribute to diverse ML projects
  • Implement research ideas
  • Improve training and deployment pipelines
  • Enhance data quality and efficiency
  • Assess and solve new ML use cases
  • Scope and design ML solutions
  • Build and improve internal ML framework
  • Automate training, evaluation, and deployment
  • Develop new ML models and architectures
  • Build and use ML tools
  • Conduct exploratory data analysis
  • Audit and auto-label data
  • Maintain ML data pipelines
  • Manage on-premise and cloud resources (GCP)

Work Experience

  • approx. 1 - 4 years

Education

  • Bachelor's degreeOR
  • Master's degree

Languages

  • EnglishBusiness Fluent

Tools & Technologies

  • Python
  • PyTorch
  • ONNX Runtime
  • TensorRT
  • SQL
  • Git
  • Linux
  • NVIDIA
  • ONNX
  • Docker
  • Containers

Benefits

Flexible Working

  • Flexible work options
  • On-site work option
  • Hybrid work option

Informal Culture

  • International team
  • No hierarchy
  • No politics

Startup Environment

  • Part of large network

Other Benefits

  • Extensive resources

Modern Office

  • No walls
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