Research Engineer

Phi Labs is Quantiphi’s R&D powerhouse, driving next-gen AI innovation with real-world impact. From pioneering advances in Generative-AI and Digital-Twins to solving complex challenges in life sciences, Phi Labs explores emerging frontiers before they become mainstream.

Good to have:

Demonstrated industry research experience will be considered as an additional bonus.

Prior R&D experience, and/or publications at top-tier ML conferences will be an advantage.

Strong classical education on math/physics/mechanics/CS/Engineering concepts will also be an advantage.

Must have:

Preferred Level of Education: Master’s or PhD

Minimum work experience required : from new graduates to 3+ yrs of research experience post graduation

Excellent in-depth understanding of ML concepts and the respective underlying mathematical know-how

Hands-on experience in developing and improving Large Language Models and related techniques (finetuning / quantization / distillation / inference optimization / model merging etc.) is a must

Knowledge of Cloud-environments like GCP/Azure, ML frameworks like PyTorch, Agent-frameworks like Langchain, ADK etc., with good experience in large scale distributed training

Excellent coding skills (Python advanced) and flexible mindset, with ability to quickly switch between & adapt to newer concepts

Ability to translate abstract highlights into understandable insights in multiple knowledge dissemination formats like blogs, presentations, paper-publications, tutorials and webinars

Stay ahead of the AI maturity curve, focusing on the upcoming areas of AI research, curate new ideas and upcoming research areas, explore multiple areas of Al research

Build rapid prototypes and conduct detailed experimental studies to prove concepts in multiple AI and Engineering domains like Generative-AI, NLP, Multimodal AI, Computer-Vision, Reinforcement Learning etc.

Work with experienced researchers and engineers to build cutting edge solutions on LLMs, Multimodal LMs, Multi-Agentic Workflows and more, resulting in various novel baselines and models.

Contribute to Q’s growth through new ideas, reusable building blocks/assets, and IP (publications & patents.

Enhance company brand through thought leadership, document the knowledge gained and disseminate to broader audience in multiple formats, working on technical content creation, publications, in conjunction with content-team and program managers .