مهندس ذكاء اصطناعي

· Develop novel state-of-the-art vision algorithms and corresponding systems, leveraging deep learning techniques.

· Research, develop and prototype advanced computer vision technologies and integration with hardware edge processors.

· Develop high-quality computer vision algorithms for localization, object detection, classification, and video analysis.

· Translate algorithms into production-level code.

· Contribute to a large code base in Python for deploying these models in production environments.

· Implement best practices for data collection, preprocessing, feature engineering, and model training, and ensure that the team follows these practices consistently

· Conduct regular code reviews and provide technical guidance and feedback to team members, ensuring that they produce high-quality code that is efficient, scalable, and maintainable.

· Interface with the Product/Project manager to develop R&D plans, proposals, intellectual property filings, commercialization strategies and other material that facilitate the innovation process.

· Collaborate with Product/Project managers in maintaining a roadmap for the team's AI projects, including identifying key milestones, timelines, and resource requirements.

· Collaborate with team members to develop, test, deploy, and maintain software/AI systems while being actively involved in product backlog grooming, sprint planning, execution, review, and retrospectives.

· Work with IT, software and security teams to deploy production grade AI solutions that comply with relevant data privacy and security regulations.

Collaborate with subject matter experts to understand their business needs and develop ML solutions that meet their requirements.

Requirements

Minimum Qualifications

• Bachelor’s degree in AI, Remote Sensing, Survey, Engineering, or any other related fields

Minimum Experience:

• Preferably 1-3 years’ experience in the same field

Job-Specific Knowledge & Skills:

· Experience developing machine learning models and neural network-based computer vision models.

· Experience deploying production grade ML and vision systems on the edge for real-time applications.

· Python Knowledge.

· Strong software engineering skills.

· Strong ability to present work and communicate ideas to technical and non-technical coworkers.

· Experience with machine learning libraries such as Tensorflow, Keras, Sklearn and others.

· Experience using OpenCV.

· Experience with git and other such versioning tools.

· Experience with DevOps cloud tools (AWS, Google Cloud etc.).

· Experience with NVIDIA Triton inference server will be plus

· Experience with MLOps tools such as Kubeflow will be a plus.

· Experience with web development frameworks (e.g Flask, Django) will be a plus

· Experience handling a large code base in python will be a plus.

· Experience developing computer vision algorithms for anomaly detection will be a plus.

Fluency in English.