About the
Role


We are seeking a
highly skilled GenAIData
Scientist with expertise in Machine
Learning (ML), Artificial Intelligence (AI), and Generative AI (GenAI) to join our team. The
ideal candidate will have a strong foundation in traditional data science
methods along with hands -on experience in building, fine -tuning, and deploying
generative AI models for business applications.

This role will
involve working closely with cross -functional teams to design, develop, and
deploy AI/ML solutions, leveraging both classical approaches (predictive
modeling, optimization, NLP, forecasting, computer vision) and cutting -edge
generative AI techniques (LLMs, diffusion models, multi -modal AI).

Key
Responsibilities


· Develop
and deploy end -to -end
ML/AI pipelines,
from data collection, preprocessing, and feature engineering to model training,
evaluation, and deployment.

· Apply traditional
ML/AI techniques (regression, classification, clustering,



recommendation systems, optimization).

· Design
and implement GenAI
solutions using large
language models (LLMs), transformers, and multimodal
architectures (text, image, audio).

· Fine -tune,
evaluate, and optimize foundation models (e.g., GPT, LLaMA, Claude, Falcon,
Reliable Diffusion) for enterprise use cases.

· Research,
experiment, and prototype cutting -edge AI solutions tailored to business
problems.

· Collaborate
with data engineers, ML engineers, and domain experts to productionize models and integrate them into
business workflows.

· Containerize
and orchestrate models and pipelines (Docker, Kubernetes).

· Stay




updated with the latest trends in AI, ML, and GenAI, and drive innovation and adoption
of new methods.

Requirements

Required
Qualifications:


· Bachelor’s
degree (B.Tech, BE, or equivalent) in Computer Science, Data Science, AI, or
related field.

· Advanced
degree (M.Tech/MS/MBA/PhD) is a plus but not mandatory.

· 3 -5
years of experience in ML/AI, with hands -on expertise in building and deploying
models.

· Functional
expertise in at least one business domain (e.g., Supply Chain, Finance,
Healthcare, Pharma, Customer Analytics, Manufacturing).

· Proficiency
in Python, PyTorch/TensorFlow, scikit -learn, Hugging Face, LangChain.

· Strong
understanding of NLP, predictive modeling, deep learning architectures (CNNs,
RNNs, Transformers).

· Experience
with cloud AI platforms (AWS, Azure, GCP) and MLOps tools (Docker, Kubernetes,
CI/CD).

· Strong
stakeholder management and ability to communicate technical insights in
business terms.