Applied Research Engineer

Job Description

Our Story Vegapay Technology is a financial technology company. It partners with banks and financial institutions to digitize its financial infrastructure. It provides users with a credit suite featuring a wide breadth of modules and no-code configuration to design, deploy, and direct their credit programs. It provides access to build financial asset products including Card Management System, LOS, LMS, Co-lending and more. Founded in 2022 by Gaurav Mittal, Himanshu Agrawal, Puneet Sharma and Abhinav Garg, the startup is a B2B digital lending and Card Management Platform. Vegapay s vision is to liberate financial institutions and fintech enterprises from every technical barrier which hinders offering a lending programme. Meet the Team Gaurav Mittal - Gaurav is the Co-Founder and the CEO of the company. He is having more than 18 yrs of experience and has worked with organisations like Zeta, Matchmove, MasterCard, Amex and ICICI Bank. Abhinav Garg - Abhinav is the Co-Founder and the Head of engineering. He is from IIT Roorkee and has more than 12 yrs of experience working with organisations like Podeum and WalmartLabs. Himanshu Agrawal - Himanshu is the Co-Founder and the Head of Technology. He is from IIT Kanpur and has more than 12 yrs of experience working with organisations like Amazon and DE Shaw. Puneet Sharma - Puneet is the Co-Founder and the Head of Product. He is from IIT Roorkee and has more than 8 years of experience working with organisations like BharatPe, Avail Finance Why This Role Matters The Applied Research Engineer will play a pivotal role in advancing Vegapay s AI-driven compliance solutions by developing novel AI/ML algorithms and ensuring their practical implementation. This role bridges the gap between research and production, focusing on algorithm development, experimentation, and optimization to enhance Tookitaki s capabilities in fraud detection, risk management, and anomaly detection. The role also involves collaborating with data scientists, engineers, and regulatory teams to create cutting-edge, regulatory-compliant AI solutions. The Hats You Will Wear Design and develop machine learning (ML) and deep learning (DL) models for various AI applications. Research and implement state-of-the-art algorithms in areas such as NLP, computer vision, reinforcement learning, and generative AI. Optimize AI models for scalability, efficiency, and deployment in production environments. Build and maintain high-quality datasets for training and evaluation. Collaborate with research scientists to publish papers, contribute to patents, and present findings at conferences. Write clean, efficient, and well-documented code to implement AI solutions. Stay updated with the latest advancements in AI, ML, and related fields. Collaborate with data engineers to work on data platform and genAI. The Perfect Fit Education : Bachelor s/Master s/Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Programming Skill s: Strong experience in Python, C++, or Java. Machine Learning Frameworks : Proficiency in TensorFlow, PyTorch, JAX, or Scikit-learn. Mathematical Foundations : Strong knowledge of linear algebra, probability, statistics, and optimization. Deep Learning & AI Concepts : Experience with NLP (transformers, LLMs), CNNs, RNNs, GANs, or reinforcement learning. Big Data & Distributed Computing : Familiarity with Apache Spark, Hadoop, and cloud platforms (AWS, GCP, Azure). Your Edge Over the Rest Experience working on real-world AI deployments in production. Contributions to AI research in academic journals, conferences (NeurIPS, ICML, CVPR, ACL, etc.). Familiarity with MLOps, containerization (Docker, Kubernetes), and AI model deployment. Hands-on experience in fine-tuning LLMs and working with open-source AI tools.