Aniket Kumar
Artificial Intelligence Engineer @Monolithic Power Systems, Inc.
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WORK HISTORY
Artificial Intelligence Engineer @Monolithic Power Systems, Inc.
San Jose, CA, US
I am working on building AI-powered applications across HR, legal, and customer support domains. I’ve architected a full-stack AI resume screening system, fine-tuned large language models for enterprise support automation, and developed a legal contract automation agent. My work involves leveraging FastAPI, Next.js, BERT, LLaMA-3, Qwen2.5, LangChain, and Ollama to design scalable solutions with semantic search, RAG, and prompt engineering that drive real-world impact.
EDUCATION
SRM IST Chennai
Bachelor of Technology - BTech, Computer Science with specialization in AIML
University of Southern California
Master of Science - MS, Artificial Intelligence
ABOUT ANIKET KUMAR
I am Aniket Kumar, currently pursuing a Master\'s degree in Computer Science with a specialization in Artificial Intelligence at the University of Southern California, expected to graduate in 2026. I previously completed my Bachelor\'s degree in Computer Science, focusing on AI and Machine Learning, which laid a strong foundation for my passion in this dynamic field.My Key Skills :1. Agentic AI Systems: Designing autonomous agents capable of executing complex tasks with minimal human intervention.2. Model Context Protocol (MCP): Implementing MCP to standardize and streamline the integration of AI models with external data sources and tools.3. Retrieval-Augmented Generation (RAG): Enhancing LLMs by integrating external knowledge sources to improve response accuracy and relevance.4. Fine-Tuning LLMs: Customizing models like DeepSeek-R1, Qwen, LLaMA, and Gemini to cater to specific tasks and domains.5. Reinforcement Learning from Human Feedback (RLHF): Applying techniques such as Group Relative Policy Optimization (GRPO) to refine model outputs based on human preferences.6. n8n Workflows: Automating complex workflows to facilitate seamless data processing and task execution.7. Multimodal AI: Integrating and processing information from multiple data sources like text, images, and audio to create a seamless user experience. Edge Machine Learning: Deploying machine learning models directly on devices to reduce latency and enable real-time processing. Small Language Models (SLMs): Utilizing compact models like Phi-3 for efficient performance on devices with limited computational resources. AI Infrastructure Optimization: Leveraging advancements in AI hardware, such as Google\'s TPU v7, to enhance model performance and efficiency. AI-Powered Software Solutions: Developing applications that integrate AI capabilities to enhance productivity and customer engagement. I am passionate about leveraging these technologies to create intelligent systems that can understand, reason, and act autonomously in dynamic environments. Seeking new challenges and collaborations, I\'m ready to bring my expertise to your team. Let\'s connect and explore the possibilities! Contact: a••••••••@gmail.com
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