AI Engineer

· 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.

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.