Proficiency in machine learning algorithms and frameworks, with specific expertise in
LLMs such as BERT, ROBERTA, XLNet, GPT, and LLama.
Extensive knowledge of Natural Language Processing (NLP) techniques and
methodologies.
Familiarity with deep learning fundamentals, including LSTM, CNN, and RNN
architectures.
Hands-on experience in developing and deploying machine learning models using
frameworks like Flask or Django.
Ability to analyze and preprocess large datasets efficiently.
Strong problem-solving skills and the ability to work independently or collaboratively
in a team environment.
Excellent communication skills to articulate complex technical concepts effectively.
Keen interest in staying updated with the latest advancements in machine learning and
artificial intelligence.
Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or
related fields.
Prior experience in implementing scalable and efficient machine learning solutions
would be advantageous.
Proficiency in deep learning fundamentals, with expertise in neural network
architectures such as CNN, MobileNet, InceptionNet, VGG16, etc.
Extensive knowledge of image processing techniques, including segmentation and
feature extraction.
Hands-on experience in developing and deploying deep learning models using
TensorFlow and PyTorch libraries.
Familiarity with object detection algorithms like YOLO and object and instance
segmentation methods.
Ability to process and analyze video data to derive meaningful insights and patterns.
Strong problem-solving skills and the ability to optimize and fine-tune deep learning
models for performance and efficiency.
Excellent understanding of computer vision principles and techniques.
Effective communication skills to collaborate with cross-functional teams and
stakeholders.
Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or
related fields.
Prior experience in implementing