Job Description:

Principal Scientist: Lead Principal Scientist - AI Research

We are seeking a Principal Scientist Generative AI & NLP to lead our research and development efforts in cutting-edge AI technologies, including Large Language Models (LLMs), multimodal AI, and agentic systems. This role is ideal for a seasoned AI researcher and technologist with a strong publication record, deep algorithmic expertise, and hands-on experience in building and optimizing large-scale AI systems under real-world constraints. You will play a pivotal role in setting the research direction, leading high-impact publications, and driving the development of scalable, production-ready AI solutions that power next-generation products.

Key Responsibilities:

1. Research Leadership:

- Define and drive the research roadmap in LLMs, multimodal AI, and Generative AI.

- Lead the authoring and publication of top-tier research papers (e.g., NeurIPS, ICML, ACL, CVPR).

- Stay at the forefront of AI advancements and translate research into practical, scalable solutions.

2. Algorithm & System Design:

- Design and optimize novel algorithms for generative modeling, NLP, and agentic AI under system and compute constraints.

- Lead the development of high-performance training pipelines for large-scale models, including distributed training and inference optimization.

3. Product & Platform Development:

- Architect and implement end-to-end GenAI systems, including prompt orchestration, retrieval-augmented generation (RAG), and agentic workflows.

- Collaborate with engineering, product, and data science teams to integrate AI solutions into production environments.

- Build and maintain highly scalable backend microservices and real-time inference systems on cloud platforms (AWS, GCP, Azure).

4. Mentorship & Collaboration:

- Mentor junior scientists / engineers in GenAI best practices and research methodologies.

- Work cross-functionally to align AI initiatives with business goals and customer needs.

Required Qualifications:

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

- 10-15 years of industry and/or academic experience in AI/ML, with 7+ years in NLP and Generative AI.

- Demonstrated leadership in publishing top-tier research such as NeuralIPS, ICLR, ICML, AAAI, and CVPR in LLMs, multimodal models, or related areas.

- Proven experience in large-scale model training, optimization, and deployment.

- Expertise in Python, with proficiency in frameworks such as Hugging Face Transformers, TensorFlow, PyTorch, Keras, JAX.

- Deep understanding of LLMs, multimodal AI, embedding models, vector databases, and agentic AI.

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

- Strong system design skills, including distributed systems, data pipelines, and API development.