AI/ML/Gen AI Data Scientist

Job Overview:

We are looking for a highly skilled AI/ML/Gen AI Data Scientist with expertise in Generative AI, Machine Learning, Deep Learning, and Natural Language Processing (NLP). The ideal candidate should have a strong foundation in Python-based AI frameworks and experience in developing, deploying, and optimizing AI models for real-world applications.

Key Responsibilities:

Develop and implement AI/ML models.

Work with Deep Learning architectures like Transformers (BERT, GPT, LLaMA) and CNNs/RNNs.

Fine-tune and optimize Large Language Models (LLMs) for various applications.

Design and train custom Machine Learning models using structured and unstructured data.

Leverage NLP techniques such as text summarization, Named Entity Recognition (NER).

Implement ML pipelines and deploy models in cloud environments (AWS/GCP/Azure).

Collaborate with cross-functional teams to integrate AI-driven solutions into business applications.

Stay updated with latest AI advancements and apply innovative techniques to improve model performance.

Required Skills & Qualifications:

3+ years of experience in AI/ML, Deep Learning, and Generative AI.

Strong proficiency in Python and ML frameworks like TensorFlow, PyTorch, Hugging Face, Scikit-learn.

Hands-on experience with NLP models, including BERT, GPT, T5, LLaMA, and Stable Diffusion.

Expertise in data preprocessing, feature engineering, and model evaluation.

Experience with MLOps, cloud-based AI deployment, and containerization (Docker, Kubernetes).

Knowledge of vector databases and retrieval-augmented generation (RAG) techniques.

Ability to fine-tune LLMs and work with prompt engineering.

Strong problem-solving skills and ability to work in agile environments.

Educational Requirements:

Bachelor's, Master's, or PhD in Computer Science/Artificial Intelligence/Information Technology

Preferred Skills (Good to Have):

Experience with Reinforcement Learning (RLHF) and multi-modal AI.

Familiarity with AutoML, Responsible AI (RAI), and AI Ethics.

Exposure to Graph Neural Networks (GNNs) and time-series forecasting.

Contributions to open-source AI projects or research papers.

Why Join Us?

Work on cutting-edge AI projects that shape the future.

Collaborate with top AI experts in an innovative environment.

Opportunity for continuous learning, growth, and upskilling.