Game Tester Freshers Walk-in Drive - GlobalStep Pune

Salary

6.3-12.6 LPA

Location

remote

Highlights

Hands-on experience, model training & evaluation, dataset preparation, real-time inference optimization

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Description

Embark on an exciting journey as a Computer Vision/AI Engineer, perfect for final-year students and recent graduates. This role offers hands-on experience in building real-world AI systems and working alongside experienced professionals.

Your responsibilities will include training and evaluating models for object detection, segmentation, classification, and tracking. You'll be involved in dataset preparation, model optimization, and deployment. This involves preprocessing data, performing quality checks, running experiments with advanced frameworks like YOLO and Mask R-CNN, and integrating models for real-time inference.

Key Responsibilities:

• Train and evaluate AI models using CNNs, computer vision, deep learning, and machine learning.
• Support dataset preparation, augmentation, annotation, and quality checks to ensure high model accuracy.
• Work with existing pipelines: testing, benchmarking, debugging, and iterative improvements.
• Document findings from experiments run on various models, including YOLO and Mask R-CNN.
• Optimize models for real-time inference in applications such as video analysis and frame-by-frame damage detection.

This is an ideal position to develop your skills in Python programming, deep learning frameworks like PyTorch and TensorFlow, and classical image processing. We're looking for individuals with strong fundamentals in Python, machine learning concepts, and linear algebra basics. Additionally, experience in OpenCV and NumPy would be beneficial.

As a Computer Vision/AI Engineer intern/fresher, you'll have the opportunity to work in a dynamic environment, collaborate across teams, and contribute to cutting-edge projects. Join us for an enriching professional journey!

Skills

Python-Programming Deep-Learning-Frameworks Computer-Vision OpenCV Model-Optimization