Job Description :

We are seeking a forward-thinking AI Developer with expertise in Generative AI, Machine Learning, Data Science, and Advanced Analytics. In this role, you will design, optimize, and deploy scalable AI solutions that power automation, personalization, and decision intelligence. You will closely collaborate with data engineers, product leaders, and business stakeholders to develop production-grade AI systems aligned with the latest enterprise AI trends such as LLM, prompt engineering, multimodal AI, and trustworthy/ethical AI practices.

This is a unique opportunity to work at the forefront of AI innovation, shaping high-impact solutions that address real-world challenges across industries.

Key Responsibilities :

- Design and deploy advanced Generative AI models including LLMs, diffusion models, and multimodal architectures.

- Develop and fine-tune ML/DL solutions for NLP, computer vision, time-series forecasting, and predictive analytics.

- Implement RAG pipelines, embeddings-based search, and knowledge graph integrations to enhance context-aware AI applications.

- Stay ahead of AI research, industry trends, and tools (multi-agent systems, federated learning, privacy-preserving ML).

What we are looking for :

- Strong programming background in Python (primary), R & Familiar with Object Oriented Programming Language.

- Proficiency in any of the framework PyTorch, TensorFlow, SAS, ChemBerta.

- Expertise in Machine Learning & Deep Learning.

- Strong grounding in mathematics & applied statistics (linear algebra, probability, optimization).

Qualifications :

- Bachelors, Masters, in Computer Science, Artificial Intelligence, Data Science, or related fields. We also welcome PhD scholars.

- 06 years of proven experience into AI development, optimization, and production deployment.

Preferred / Nice to Have :

- Someone who is passionate about GEN AI is ideal candidate & did Research contributions or open-source AI project contributions.

- Exposure to multimodal AI, agent-based systems, or reinforcement learning.

- Knowledge of AI safety, interpretability frameworks, and responsible AI practices.