Machine Learning Engineer - Computer Vision

Experience : 5+ years

Location : Bangalore

Employment Type : Full-time

About the Role :

We are looking for a hands-on Computer Vision / Video ML Engineer who can build, deploy, and scale real-world ML systems involving images and video.

The ideal candidate has strong experience in computer vision, video analytics, object detection, tracking, or activity recognition, along with excellent Python and PyTorch skills. You will own important technical problems end-to-end - from model development and experimentation to production deployment and optimization.

What You'll Do :

• Design, develop, and deploy computer vision and video ML systems for real-world applications.

• Build and improve models for object detection, object tracking, activity recognition, and video understanding.

• Work with large-scale image and video datasets for training, evaluation, and model improvement.

• Develop ML pipelines using Python and PyTorch.

• Take models from research/prototype stage to production, including testing, optimization, deployment, and monitoring.

• Improve model accuracy, latency, reliability, and scalability for production use cases.

• Debug and solve challenging ML and computer vision problems independently.

• Collaborate with product, engineering, and other teams to translate business problems into practical ML solutions.

• Take end-to-end ownership of critical technical projects and drive them to completion.

What We're Looking For :

• 5+ years of hands-on experience in Machine Learning, with significant experience in Computer Vision / Video ML.

• Proven experience building and launching computer vision or video-based ML systems.

• Strong understanding and hands-on experience with :

• Object Detection

• Object Tracking

• Activity Recognition

• Video Analytics / Video Understanding

• Strong programming skills in Python.

• Strong hands-on experience with PyTorch and modern deep learning frameworks.

• Experience taking ML models from development to production.

• Strong understanding of model training, evaluation, optimization, and deployment.

• Demonstrated ability to independently own and deliver high-impact technical work.

• Strong problem-solving and debugging skills.

Good to Have :

• Experience working with real-time or large-scale video processing systems.

• Experience with model optimization for latency, throughput, or compute efficiency.

• Experience with GPU-based inference and deployment.

• Familiarity with tools and frameworks used for production ML systems.

• Experience working with cloud-based ML infrastructure.