Deep Learning Software Developer

3 days ago

Islamabad, Islamabad, Pakistan beBee Careers Full time

The ideal candidate for this position possesses exceptional skills in designing, developing, and deploying machine learning models that drive business value and solve complex problems. As a key member of our team, you will be responsible for leveraging your expertise in machine learning and computer vision to develop innovative solutions that meet or exceed customer expectations.

Key Responsibilities:
  1. Develop and implement machine learning models that integrate computer vision techniques for indoor mapping solutions.
  2. Oversight and management of cloud-based machine learning infrastructure to ensure scalability, reliability, and performance.
  3. Leadership of external data annotation teams, guiding the data labeling process to ensure accurate and high-quality training datasets.
  4. Development of rule-based systems that enhance the performance of machine learning models and support decision-making processes.
  5. Evaluation, refinement, and deployment of machine learning models to meet established quality and performance standards.
Requirements:
  1. Extensive experience in Python programming, specifically in the context of machine learning and data science.
  2. Proven track record of developing and deploying machine learning models that incorporate image processing and computer vision techniques.
  3. Hands-on expertise in leading deep learning frameworks such as PyTorch and TensorFlow.
  4. Familiarity with cloud platforms, particularly Google Cloud Platform (GCP), and API development.
  5. In-depth knowledge of machine learning infrastructure, encompassing model deployment, maintenance, and scaling.
  6. Strong leadership experience in managing cross-functional teams and driving successful project outcomes.
  7. Portfolio demonstrating expertise in rule-based systems development and deployment.
  8. Advanced understanding of machine learning model scaling, optimization, and performance enhancement.
  9. Familiarity with MLOps and CI/CD pipelines for efficient machine learning model deployment.

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