Sunil Thapa (Sunil)

With over 4 years of experience in AI engineering, I specialize in Natural Language Processing (NLP), Machine Learning, and deploying innovative AI-driven solutions. I have expertise in developing and optimizing LLM-based systems, including retrieval-augmented generation (RAG), to enhance NLP tasks. My skill set includes cloud infrastructure management (AWS, GCP, Azure), building scalable and fault-tolerant environments, and automating robust data pipelines using big data technologies like Hadoop, Spark, and Hive.

I am experienced in diverse machine learning applications, from recommendation systems to real-time object detection models, and have a strong focus on NLP solutions, such as sentiment analysis, document summarization, and multilingual chatbots. Proficient in deploying CI/CD pipelines with Terraform and GitHub Actions, I also excel in data visualization using Tableau and Power BI to drive data-informed decision-making. Passionate about research, I have contributed to advancements in underrepresented languages through projects like NepaliBERT.

With a collaborative mindset and commitment to continuous learning, I deliver impactful AI solutions that align with business goals while mentoring teams to enhance technical capabilities.

• Over 4+ years of experience in AI Engineering with a strong focus on Natural Language Processing (NLP), Machine Learning, and deploying AI-driven solutions.
• Expertise in developing and optimizing LLM-based systems, with proven ability to implement innovative approaches like retrieval-augmented generation (RAG) to enhance NLP tasks.
• Strong proficiency in cloud infrastructure management (AWS, GCP, Azure) and ensuring scalable, fault-tolerant environments for AI models and systems.
• Experienced in building and automating robust data pipelines, leveraging big data technologies such as Hadoop, Spark, and Hive to streamline data processing and analytics workflows.
• Skilled in applying a wide array of machine learning techniques to solve real-world challenges, including building recommendation systems, face-attendance systems, and real-time object detection models.
• Specialized in NLP solutions, including sentiment analysis, document summarization, and building multilingual chatbots, leading to improved user engagement and experience.
• Proficient in deploying CI/CD pipelines with Terraform and GitHub Actions, significantly enhancing deployment efficiency and reducing system downtime.
• Passionate about research and innovation, with published work on NepaliBERT and other cutting-edge NLP models, contributing to advancements in language processing for underrepresented languages.
• Adept at collaborating with diverse teams to deliver AI-driven solutions that align with business goals and exceed client expectations.
• Strong communicator with an emphasis on data-driven decision-making, using data visualization tools like Tableau and Power BI to present actionable insights.
• A proactive mentor and team player, dedicated to continuous learning and enhancing the technical capabilities of teams.

As an AI Engineer at AgilePitch, I specialize in developing and deploying machine learning models, with a focus on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) techniques. My work has led to a 25% improvement in model accuracy and a 40% increase in data processing speed. By integrating self-corrective RAG models, I improved factual accuracy in document retrieval by 28%.

I have also optimized data pipelines, boosting data processing efficiency by 35%. Additionally, I have leveraged AWS services like S3, Lambda, and CloudWatch to enhance system reliability and operational efficiency by 13%. My work directly contributed to a 30% increase in model performance and overall customer satisfaction.