Research Engineer(Gen AI Research)

Quantiphi is an award-winning AI-first digital engineering company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed. Quantiphi has seen 2.5x growth YoY since its inception in 2013, growing to 4000+ team members globally.

For more details visit: http://www.quantiphi.com/

Phi Labs

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.

Team: Gen-AI Research team, within Phi Labs

Role Level: Research Engineer

Responsibilities

• 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

Requirements

The position involves working with a diverse, lively, and proactive group of nerds who are constantly raising the bar on translating the latest AI research into tangible reusable assets for the community. Hence this would require a high level of conceptual understanding, attention to detail and agility in terms of adaptation to new technologies.

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.

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.