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Senior Machine Learning Engineer

Posted 5 days agoViewed

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💎 Seniority level: Senior, 5+ years

🔍 Industry: Technology

🏢 Company: ABBYY👥 1001-5000💰 over 3 years agoCommunications InfrastructureAnalyticsData VisualizationSoftware

⏳ Experience: 5+ years

Requirements:
  • MS or PhD in Computer Science, Engineering, Mathematics, or related field.
  • 5+ years of experience in Machine Learning/AI.
  • Strong track record of shipping computer vision models to production.
  • Deep expertise in computer vision and deep learning.
  • Expert knowledge of computer vision techniques and architectures.
  • Deep expertise in modern deep learning architectures for visual and multimodal tasks.
  • Strong programming skills in Python and proficiency with PyTorch or equivalent frameworks.
  • Experience with cloud platforms and MLOps tools.
  • Demonstrated ability in building and optimizing training pipelines.
  • Strong background in image processing and visual computing.
  • Experience leading technical projects.
  • Strong problem-solving and analytical skills.
  • Excellence in cross-functional collaboration and technical communication.
  • Ability to translate complex technical concepts to various audiences.
Responsibilities:
  • Develop and optimize state-of-the-art computer vision and multimodal models.
  • Design and implement advanced model architectures for visual understanding tasks.
  • Create robust evaluation frameworks and testing methodologies.
  • Drive technical improvements in model performance and efficiency.
  • Research and evaluate new approaches in computer vision and multimodal learning.
  • Implement novel computer vision algorithms and techniques.
  • Lead technical implementation of ML projects.
  • Drive architectural decisions for model development.
  • Review code and model architectures.
  • Contribute to technical planning and decision-making.
  • Support cross-functional collaboration with product and infrastructure teams.
  • Implement scalable training and evaluation pipelines for computer vision models.
  • Build efficient visual data processing workflows.
  • Develop monitoring solutions for production ML systems.
  • Optimize model performance and resource utilization.
  • Support deployment and production maintenance.
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