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