Description :

Role : Principal Scientist (AI, ML & Generative AI)

Location : Bangalore

Experience : 10 - 15 Years

Job Summary :

We are seeking a visionary Principal Scientist to lead our Artificial Intelligence research and implementation strategy. In this role, you will bridge the gap between cutting-edge academic research and large-scale industrial application. You will be the technical authority for our Generative AI roadmap, overseeing the development of LLMs, multimodal systems, and agentic workflows that solve complex, real-world problems.

Responsibilities :

- Technical Leadership : Drive the long-term R&D roadmap for AI/ML, focusing on Generative AI, LLMs, and Multimodal models.

- Model Innovation : Lead the end-to-end lifecycle of large-scale model training - from data curation and pre-training to fine-tuning (SFT, RLHF) and optimization for production.

- Architectural Oversight : Design robust, scalable system architectures including RAG pipelines, vector databases, and autonomous agentic frameworks.

- Research & Publication : Maintain the company's technical edge by publishing original research in top-tier venues (e.g., NeurIPS, ICML, ICLR, CVPR) and patenting novel methodologies.

- Strategic Collaboration : Partner with Product and Engineering leadership to translate business requirements into high-impact AI solutions.

- Mentorship : Act as a force multiplier by mentoring Staff and Senior Scientists, fostering a culture of technical excellence and continuous learning.

Required Qualifications :

- Education : Ph.D. or Masters degree in Computer Science, Machine Learning, Mathematics, Computational Linguistics, or a related quantitative field.

- Industry Experience : 10 - 15 years of total experience in AI/ML, with a minimum of 7 years dedicated to NLP and Generative AI.

Technical Stack :

- Languages : Expert-level Python.

- Frameworks : Deep proficiency in PyTorch, TensorFlow, JAX, and Hugging Face Transformers.

- LLM Ecosystem : Extensive experience with LangChain/LlamaIndex, DeepSpeed, Megatron-LM, and vector stores (Pinecone, Milvus, Weaviate).

Core Expertise :

- Proven track record in distributed training of models with billions of parameters.

- Experience with LLMOps/MLOps tools (Weights & Biases, MLflow, SageMaker, or Vertex AI).

- Deep understanding of distributed systems and API design for AI-first applications.

Preferred Attributes :

- Active contributor to open-source AI projects or a strong portfolio of peer-reviewed publications.

- Experience in optimizing model inference (Quantization, Distillation, FlashAttention) for low-latency production environments.

- Demonstrated ability to navigate the "Responsible AI" landscape (bias mitigation, safety guardrails, and explainability).