Y

Computer Vision Engineer

yo hr consultancy • Argentina
Remote
This Job is No Longer Active This position is no longer accepting applications

Job Description

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: computer vision,cnns,tensorflow,tensorflow or pytorch,tensorflow/pytorch,segmentation,python for data science,models,pytorch,cloud platforms (aws, azure, google cloud),azure,python,computer science,machine learning,image filtering,algorithms,feature extraction,convolutional neural networks (cnns),processing,opencv,large language models (llms),convolutional neural networks,image recognition,engineering,deep learning,mobile coding,mobile coding domain,object detection,aws,image processing,keras,deep learning models,google cloud,ai-driven solutions,cloud platforms,object tracking

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