About the Role / About the Job
- 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, ensuring 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 materials 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.
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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 versioning tools.
- Experience with DevOps cloud tools (AWS, Google Cloud, etc.).
- Experience with NVIDIA Triton inference server will be a 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.
