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.

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.