Data Scientist – Al/ML

Job Description

We are seeking a highly skilled and motivated Data Scientist with hands-on experience in Artificial Intelligence (AI), Machine Learning (ML), and Generative AI to join our growing team. The ideal candidate should have strong expertise in designing, developing, and deploying AI-powered solutions using modern machine learning frameworks, Large Language Models (LLMs), and cloud-based AI services.

This role requires a strong programming background, problem-solving skills, and experience building scalable AI/ML applications for real-world business use cases.

Key Responsibilities
Design, develop, and deploy Machine Learning and Deep Learning models for business applications.
Build and optimize Generative AI solutions using Large Language Models (LLMs).
Develop AI applications using frameworks such as LangChain and integrate them with enterprise workflows.
Train, fine-tune, and evaluate machine learning models using TensorFlow or PyTorch.
Develop robust data pipelines and perform data preprocessing using Python and SQL.
Collaborate with cross-functional teams to understand business requirements and translate them into AI-driven solutions.
Deploy and monitor AI/ML models in production environments.
Optimize model performance, scalability, and reliability.
Stay updated with the latest advancements in AI, ML, Generative AI, and cloud technologies.
Required Skills
Strong expertise in Python and SQL.
Hands-on experience with Machine Learning, Deep Learning, and Generative AI.
Experience working with Large Language Models (LLMs).
Proficiency in LangChain and LLM-based application development.
Experience with TensorFlow and/or PyTorch.
Knowledge of cloud AI services on Microsoft Azure and/or Amazon Web Services (AWS).
Strong understanding of data structures, algorithms, and statistical modeling.
Excellent analytical, problem-solving, and communication skills.
Preferred Qualifications
Experience building, deploying, and maintaining AI/ML solutions in production environments.
Familiarity with MLOps concepts, model monitoring, and CI/CD pipelines.
Experience with vector databases, embeddings, RAG (Retrieval-Augmented Generation), or prompt engineering is an added advantage.
Exposure to Docker, Kubernetes, or cloud-native deployment is a plus.
Experience
Relevant experience in Data Science, AI/ML, or Generative AI.
Candidates with proven experience in delivering production-grade AI solutions will be preferred.