Quantiphi
Location
Mumbai | India
Job description
The Role in a Nutshell: This is a great opportunity to work on cutting-edge topics within the growing Applied Research team of Quantiphi. You will investigate some of the latest trends in artificial intelligence, using the state of the art deep learning techniques, LLMs, knowledge graphs etc, develop proof of concepts, prototypes, publish your work and produce Intellectual Property (IP).
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 ML and Engineering domains like Physics-Informed Neural Networks, Neural Operators, Simulations, Reinforcement Learning, optimization etc. ● Work with experienced researchers and engineers to build cutting edge solutions, benchmark various novel baselines and models ● Contribute to Q’s growth through new ideas, reusable building blocks/assets, and IP/patents ● Enhance company brand through thought leadership, document the knowledge gained and disseminate to broader audience in multiple formats, working on technical content creation, 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 Al 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: ● Education level: Bachelor’s or Master’s degree in Mechanical/Chemical/Materials or relevant stream ● Preferred work experience: 2+ yrs of research experience post graduation (in applied ML research) ● Excellent in-depth understanding of ML concepts and the respective underlying mathematical know-how ● Hands-on experience in developing and deploying models with various deep learning architectures such as physics-informed neural networks, neural operators in engineering domains ● Excellent coding skills (Python advanced) and flexible mindset, with ability to quickly switch between & adapt to newer concepts ● Knowledge of Cloud-environments like GCP/AWS and ML frameworks like TensorFlow/PyTorch ● Ability to translate abstract highlights into understandable insights in multiple knowledge-dissemination formats like presentations, paper-publications and webinarsJob tags
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