Senior Data Scientist

4 days ago

Bengaluru, India TekIT Software Solutions Pvt. Ltd. Full time

Location : Bengaluru


Experience : 56 Years


We are seeking a highly motivated and skilled Senior Data Scientist with expertise in Computer Vision and Generative AI (GenAI) to join our AI team in Bengaluru. The ideal candidate will have strong experience in machine learning, deep learning, and natural language processing, with hands-on knowledge of deploying models at scale on cloud platforms like Azure.


Key Responsibilities :


ML & AI Model Development :


- Design, develop, and deploy models for regression, classification, and clustering problems.


- Extract insights from large datasets using both classical machine learning and deep learning methods.


Computer Vision & Deep Learning :


- Apply advanced techniques in image processing, object detection, image segmentation, and CNN architectures.


- Work with libraries and frameworks such as OpenCV, Detectron2, YOLO, and others.


- Develop deep learning solutions using TensorFlow, PyTorch, and Theano.


Generative AI & NLP :


- Experiment with Large Language Models (LLMs) like GPT, BERT, and T5.


- Build Retrieval-Augmented Generation (RAG) pipelines with chunking and indexing strategies.


- Create intelligent applications using LangChain, Haystack, and other agentic frameworks.


Cloud & Model Deployment :


- Deploy ML/DL models on cloud platforms, preferably Microsoft Azure.


- Utilize Azure ML, Docker, Kubernetes for CI/CD and scalable deployment.


Required Skills & Qualifications :


- 56 years of experience in AI/ML/Data Science with hands-on project experience.


- Proficient in Python and ML libraries such as Scikit-learn, TensorFlow, PyTorch.


- Expertise in Computer Vision using OpenCV, YOLO, Detectron2, etc.


- Strong understanding of CNNs, GANs, RNNs, and related deep learning architectures.


- Hands-on experience in NLP techniques and Generative AI frameworks.


- Experience with Azure cloud services and scalable deployment tools.


- Solid foundation in statistics, linear algebra, probability, and calculus.


(ref:hirist.tech)

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