Malik Haseeb Haider

AAngstrom Workgroup srl

• Founded and established AIOBC, a leading technology company specializing in Artificial Intelligence,NLP Deep Learning, and Computer Vision solutions.
  
• Played a dual role as a managerial CEO and a hands-on technical expert, actively involved in developing and executing the technical strategies required for project implementation.
  
• Spearheaded the development of implementation strategies for complex projects, overseeing their execution, and providing technical problem-solving expertise
  
• Continuously secured projects through technical excellence and a deep understanding of client needs, nurturing long-term client relationships.
  
• Developed and executed a strategic vision for the company projects, leading a high-performing team of 15 professionals.
  
• Oversaw financial management, budgeting, and fundraising activities to secure necessary capital for expansion and development.

PROJECTS UNDER AIOBC
VABLET
Spearheaded Vablet's R&D project for autonomous retina capture using deep learning, Orchestrated the project's technical execution, leveraging deep learning expertise to develop innovative algorithms for precise retina data capture.
Vablet CEO review :
Paul Pacun
CEO & Founder at vablet
November 3, 2022,
Malik and his team are very talented programmers. They have a very deep knowledge of AI/Tensor Flow and app development. The team has a passion for coding and is open to trying alternative paths to achieve successes. We are very pleased with the work they have done for us.
What made it very easy to work with them was their available during the US business day.
I highly recommend them.

• Developed and integrated deep learning algorithms for object detection, tracking, and classification within edge and cloud-based surveillance systems.
• Designed and optimized system architecture, enabling seamless integration of hardware and software components for enhanced real-time video analysis.
• Managed large-scale surveillance data efficiently, ensuring robust data storage, retrieval, and cloud-based accessibility for remote monitoring and analysis.

Nodeasset

• Integrated Kubeflow and SageMaker Pipelines to automate end-to-end machine learning workflows, from data preprocessing to model deployment.
• Orchestrated distributed training across multiple nodes and GPUs, significantly reducing training times for machine learning models on large datasets.
• Established Kubernetes clusters on Azure for distributed machine learning, optimizing for scalability and high availability.

• Worked on Deep learning systems and self-running artificial intelligence (AI) software to automate predictive models.
• Developed ML algorithms to analyze huge volumes of historical data to make predictions.
• Ran Deep learning learning tests and experiments by implementing appropriate ML algorithms.
• Turned unstructured data into useful information by auto-tagging images and text-to-speech conversions.