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Dugyala Ajith Kumar
Founding Machine Learning Engineer @4Minds
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WORK HISTORY
Founding Machine Learning Engineer @4Minds
Dallas, TX, US
Founding Machine Learning Engineer responsible for architecting and delivering production-grade LLM systems and knowledge-graph-driven reasoning platforms from the ground up.Designed and built an agentic, low-latency Graph-RAG architecture that augments LLMs with real-time knowledge graph retrieval, enabling context-aware reasoning over risk, compliance, and regulatory data.Led development of a knowledge-graph–powered AI platform deployed for one of the world’s largest accounting firms, supporting real-time decision intelligence and regulatory insight generation.Built an LLM-as-a-Service platform supporting scalable, multi-node training and inference workflows for foundation models.Implemented Supervised Fine-Tuning (SFT) pipelines integrated with GRPO, LCPO, DPO, and RLHF techniques to improve mathematical reasoning, alignment, and language understanding.Developed high-throughput, low-latency LLM inference systems, tightly integrated with agent-based RAG pipelines for real-time, context-rich responses.Applied JAX-based training and optimization for efficient large-scale fine-tuning and experimentation across distributed environments.Extended core pipelines to support multimodal reasoning (text + image), enabling richer semantic retrieval and cross-modal understanding.Collaborated closely with product, infrastructure, and leadership teams to translate research prototypes into beta-ready, production systems.Core TechnologiesLLMs • Graph-RAG • Knowledge Graphs • JAX • SFT • DPO • GRPO • LCPO • RLHF • Multimodal AI • Distributed Training • Low-Latency Inference • Agentic Systems
EDUCATION
Gokaraju Rangaraju Institute of Engineering and Technology
Bachelor of Technology - BTech, Computer Programming
University of North Texas
Master's degree, DataScience
ABOUT DUGYALA AJITH KUMAR
Machine Learning Engineer focused on building agentic AI systems, GraphRAG architectures, and scalable LLM platforms that solve complex enterprise problems through intelligent reasoning over data.As a Founding Machine Learning Engineer at 4Minds.AI, I design and deploy production-grade AI systems that combine large language models, knowledge graphs, and agentic frameworks to enable reliable reasoning across large and complex enterprise knowledge bases. My work focuses on developing GraphRAG architectures that integrate structured knowledge graphs with LLM reasoning, enabling organizations to extract actionable insights from regulatory, compliance, and operational data.I specialize in building end-to-end AI systems that move beyond prototypes into real-world enterprise deployment, solving problems such as large-scale knowledge discovery, decision intelligence, and automated reasoning over structured and unstructured data.My work spans the full stack of modern AI infrastructure, including:• Agentic AI systems and autonomous reasoning frameworks• GraphRAG and knowledge-graph–augmented LLM architectures• LLM fine-tuning and alignment (SFT, DPO, GRPO, LCPO, RLHF)• Distributed training and high-performance inference systems• Multimodal AI and semantic retrieval pipelinesRecently, I have been developing agentic frameworks for GraphRAG, where LLM-powered agents dynamically retrieve, analyze, and synthesize knowledge from multiple sources to solve complex enterprise workflows. These systems are designed to support decision intelligence, risk analysis, and domain-specific reasoning at scale.
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