Research Engineer -LLM

About Company:

Quantiphi is an award-winning Applied AI and Big Data software and services 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.

About the Unit:

Applied-Research is an R&D practice at Quantiphi, focused on unraveling the frontiers of AI technologies with Applied ML at its core. With a multifaceted R&D strategy, we tackle ideating and building innovative solutions to cutting edge challenges, with advanced prototyping and scalable proofs of concept. Strengthened by the strategic partnerships working towards a generalized goal, we strive to leverage and demonstrate the major advances in AI to understand and transform the way humans collaborate with AI-systems in the near future.

Role: Research Engineer

Experience: 1-3years

Location: Mumbai/Bangalore

Responsibilities:

• Working with structured and unstructured data to build Traditional and Deep-Learning based models
• Explore multiple areas of AI research, old and new, and develop end-to-end ML pipelines to solve use cases
• Build rapid prototypes and conduct detailed experimental studies to prove concepts in multiple ML domains like Computer-Vision, NLP, Reinforcement Learning etc., in a well defined time-bound environment
• Work with Solution-Architects to build cutting edge solutions, benchmark various baselines and techniques
• Document the knowledge gained and disseminate to broader audience in multiple formats, working on technical content creation and publication, 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.

• Excellent in-depth understanding of ML concepts and the respective underlying mathematical know-how
• Hands-on experience in developing and deploying models in multiple ML areas like Computer-Vision, NLP, LLM, etc.
• Knowledge of Cloud-environments like GCP/AWS and ML frameworks like TensorFlow/PyTorch, with good experience in large scale distributed training.
• Excellent coding skills 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.
• Prior R&D experience, and/or publications at top-tier ML conferences will be a huge advantage.