Data Scientist - Artificial Intelligence/Machine Learning

Job Description :

We are seeking an experienced AI ML Engineer/AI Data Scientist to join our team, with a strong background in Artificial Intelligence and Machine Learning. The ideal candidate will have 4 -7 years of experience in AI/ML and a proven track record of designing and deploying deep learning concepts to generate business value.

Key Responsibilities :

• Designing deep learning concepts and deploying machine learning solutions to generate business value

• Applying statistical and calculus concepts to drive business outcomes

• Working in the domains of Natural Language Processing (NLP) and/or Computer Vision (CV)

• Utilizing machine learning techniques like Random Forest, Support Vector Machine, and Gradient Boosting Machine

• Applying deep learning techniques across Recurrent Neural Networks, Convolutional Neural Networks, and Transformer Architectures

• Developing and deploying Generative AI techniques like RAG, Agentic Workflows, and Graph RAG

**Required Skills :

• Experience : Experienced AI Scientist with 4 - 6 years of experience in AIML.

• Design : Designing deep learning concepts.

• Mathematics : Good in Statistical and Calculus concepts.

• Domains : Applied in the domains of Natural Language Processing (NLP) and / or Computer Vision (CV).

• Deployment : Generative AI and deploying Machine Learning (ML) solutions to generate business value.

• Statistical Methods : Solid theoretical and practical knowledge of some or most econometric/statistical methods like Linear Regression, Logistic regression, Generalized Linear Model, Survival Analysis, Sampling

Techniques, Time Series Analysis, CART, CHAID, Clustering, Discriminant Analysis, Principal Component Analysis, Factor Analysis, Multidimensional Scaling etc.

• Machine Learning : Machine Learning techniques like Random Forest, Support Vector Machine, Gradient Boosting Machine, XGBoost etc.

• Deep Learning : Deep Learning techniques across Recurrent Neural Networks, Convolutional Neural Networks etc. and Transformer Architectures as applied in the domains of Natural Language Processing (NLP) and / or Computer Vision (CV) with a consistent track record of building and successfully deploying Machine Learning solutions with demonstrable value to the organization.

• Generative AI : Generative AI techniques like RAG, Agentic Workflows, Graph RAG, Model Tuning etc.