AI/Machine Learning Developers

Langchain and RAG-Based Systems (e.g., LLamaindex): Familiarity with Langchain and RAG-based systems, such as LLamaindex, will be a significant advantage. Work on the design and implementation of systems that leverage Langchain and RAG-based approaches for enhanced performance and functionality.

LLM Integration with Vector Databases (e.g., Pinecone): Experience in integrating large language models with vector databases, such as Pinecone, for efficient storage and retrieval of information. Optimize the integration of LLMs with vector databases to ensure high-performance and low-latency interactions.

Natural Language Processing (NLP): Expertise in NLP techniques such as tokenization, named entity recognition, sentiment analysis, and language translation. Experience with NLP libraries and frameworks like NLTK, SpaCy, Hugging Face Transformers

Computer Vision: Proficiency in computer vision tasks such as image classification, object detection, segmentation, and image generation. Experience with computer vision libraries like OpenCV, PIL, and frameworks like TensorFlow, PyTorch, and Keras.

Deep Learning: Strong understanding of deep learning concepts and architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Proficiency in using deep learning frameworks like TensorFlow, PyTorch, and Keras. Experience with model optimization, hyperparameter tuning, and transfer learning.

Data Manipulation: Strong skills in data manipulation and analysis using libraries like Pandas, NumPy, and SciPy. Proficiency in data cleaning, preprocessing, and augmentation techniques.

Experience: 01 - 02 Years

Education: B.TECH-CS/IT/MCA