Computer Vision Engineer

Computer Vision Engineer - LLM

Experience: 2 - 15 Years

Location- Permanent Remote Anywhere in the world

Contract Duration: 6 Months

Opportunity- Full Time, 8 hours, 5 hours Mandatory overlap with PST

Total Years Of exp- 2+ years Mandatory

Mandatory Skills- Python: min 2yrs, Python for Data Science: min1 yr, Computer Vision: min1 yr, PyTorch: min 1 yr, OpenCV: min 1 yr, Tensorflow: min 1 yr, Image Recognition: min 1 yr

Key Skills: Computer Vision, Python, Pytorch, OpenCV, Image Recognition

Job Responsibilities

• Develop and maintain machine learning models, with a focus on computer vision algorithms.
• Implement image processing techniques such as object detection, segmentation, and image classification using Convolutional Neural Networks (CNNs).
• Work with TensorFlow or PyTorch to develop, train, and deploy vision models.
• Utilize OpenCV for tasks like feature extraction, image filtering, and object tracking.
• Collaborate with cross-functional teams to enhance AI-driven solutions in the mobile coding domain.
  
  



Job Requirements

• Bachelor’s/Master’s degree in Engineering, Computer Science, or a related field.
• At least 2+ years of experience as a Python-focused Engineer.
• Expertise in image processing and computer vision algorithms using CNNs.
• Strong experience with TensorFlow/PyTorch for developing, training, and deploying vision models.
• Proficiency in OpenCV for image processing tasks.
  
  

Nice To Have

• Experience with Keras for quick prototyping of deep learning models.
• Familiarity with Large Language Models (LLMs) and their applications in AI.
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
  
  

Skills: google cloud,deep learning,collaboration,computer vision,object tracking,cross-functional team collaboration,python for data science,tensorflow or pytorch,engineering,feature extraction,aws,object detection,algorithms,models,cnns,convolutional neural networks,opencv,machine learning,mobile coding,tensorflow/pytorch,image processing and computer vision algorithms using cnns,cnn,developing, training, and deploying vision models,cross-functional collaboration,tensorflow,image filtering,cloud platforms,ai-driven solutions,processing,llms,azure,large language models (llms),keras,aws, azure, or google cloud,pytorch,convolutional neural networks (cnns),segmentation,python,image processing techniques,deep learning models,image recognition,cloud platforms (aws, azure, google cloud),image processing,computer science,mobile coding domain,opencv for tasks like feature extraction, image filtering, and object tracking