Machine Leaning Engineer

3 days ago

Lahore, Punjab, Pakistan Code District Full time 120,000 - 240,000 per year

Main tasks and responsibilities

  • Develop computer vision and deep learning applications related to object detection, object segmentation and activity/action detection.
  • Scientific thinking and the ability to invent, implement, and lead technology developments in the field of computer vision and machine learning.
  • Dedicated to delivering Machine Learning projects.
  • Utilizing existing hardware and images in addition to new image data gathering techniques to produce innovative image analysis models and algorithms.
  • Lead the ideation, prototyping, and development of AI software.
  • Demonstrate expertise in solving computer vision problems.
  • Develop deep learning and traditional machine learning algorithms.
  • Design and develop scalable software architectures.
  • Demonstrate ongoing understanding of Machine Learning technologies in current marketplace and how they can be applied to the business.
  • Facilitate design and deployment of vision hardware equipment needed for image data gathering.
  • Create and maintain data pipeline architecture for ML algorithm development.

Requirements

  • MS or PhD in Computer Science, Engineering, Mathematics or Statistics, with specialization in computer vision and deep learning.
  • Minimum 2 years of industrial experience in developing and deploying Computer Vision and Deep Learning applications in Production at scale.
  • Experience in software development, integration with deep learning algorithms and deployment in production.
  • Proficiency in scientific understanding and implementation of deep learning architectures in Computer vision (Image classification, object detection, segmentation, pose estimation) from ideation to productionized deployment.
  • Software development in Python, Deep learning (Tensorflow and Pytorch), Machine Learning libraries (OpenCV, Scikit-learn, NumPy, Pandas) and Data Analytics/Reporting.
  • DevOps: Code Management, Version Control, Code Review, CI/CD, Configuration Management, Monitoring, Containerization
  • MLOps: Experiment Management (Model Versioning, Parameter Versioning, Model Performance Metrics), Model Integration, Serving, Deployment, Testing and Continuous Monitoring
  • DataOps: Data Gathering, Annotation, Quality, Visualization, Versioning, and Engineering.
  • Ability to read scientific publications, understand and implement proposed solution.
  • Excellent written and spoken communication skills.
  • Self-driven and strong problem-solving skills.
  • Team work.
  • Strong analytical skills and process focus

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