Apurv Singh

Background

About Apurv Singh

I am a Generative AI and Machine Learning professional with a rich blend of academic rigor from Carnegie Mellon University and hands-on experience in industry-leading projects. My journey has taken me from the role of a Software Engineer at Philips, developing critical safety software and UI solutions, to pioneering generative AI applications at LivaNova. My work as a Generative AI and Machine Learning Intern at LivaNova has been transformative, leading initiatives to develop Conversational AI and enhanced search functionalities using GPT models. This included leveraging my skills in Python, C++, and Java, combined with a deep understanding of deep learning and neural networks, to empower teams with AI-driven insights and decision-making tools. In my academic pursuits at Carnegie Mellon, I am delving into Public Policy & Management with a focus on Data Analytics, where I am honing my skills in data science, machine learning, and policy analysis. My work here includes advanced coursework in computer vision, neural networks, data warehousing, and AI, positioning me at the forefront of tech-driven policy development. Previously, I've tackled high-impact roles in software engineering and machine learning, handling critical engineering issues at Philips and driving machine learning innovation at AfterShoot. My skill set spans across various domains including image processing, supervised and unsupervised learning, database management, and software architecture, making me a versatile asset in technology-driven environments. Looking For: I am actively seeking roles that challenge me to apply my skills in software engineering, machine learning, data science, and Generative AI to create innovative solutions. Skills: • Languages: C#(WPF, ASP.NET), Java, C++, Python (Pandas, NumPy, TensorFlow, PyTorch). • Technologies: Deep Learning, Image Processing, Transformers, Supervised Learning, Unsupervised Learning, Database Management, Data Science, Data Visualization, Natural Language Processing (NLP), Transformers, AWS, GCP, Data Pipelines, Reinforcement Learning (RLHF), Supervised Fine Tuning (SFT) • Other: SAFe Agile, MVC, Microservices, Object-Oriented Programming, GCP, AWS, JavaScript, Node.js, Large Language Models (LLM), Solutions Engineering, Chatbot Development, Software Architecture, High-Performance Computing (HPC), API Development, React.js, HTML, Llama, ChatGPT, Sagemaker, GPU