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.

Public

Key Responsibilities

• 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.

• 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.

• 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).

• 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 Master’s 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 NeruralIPS,

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.