Vishal Singh

About Vishal Singh

I work on ML and GenAI systems at the intersection of NLP, graph learning, and large-scale analytics, with a focus on reliability, performance, and real-world decision impact.My work spans LLM-based systems such as RAG and agentic workflows, embedding and retrieval pipelines, anomaly detection, and real-time inference, deployed across AWS and hybrid cloud environments. I’m comfortable moving between research-heavy problems and the engineering constraints required to ship and sustain ML systems in production.I bring a research-driven mindset shaped by work in vision, NLP, and graph-based learning, with particular interest in structured and relational data. I care less about models that look impressive in isolation and more about systems that remain accurate, explainable, and stable under real operating conditions.

Experience

1. Associate Manager (Senior Data Scientist Tmt Vertical)

   Tredence Inc.

   Sep 2025 — Present · Hyderabad, IN

   Data Science & Applied ML- Working on applied ML and analytics use cases within the TMT domain, spanning forecasting, anomaly detection, and decision-support systems- Contributed to exploratory analysis and early-stage solution design for dashboards and monitoring use cases.GenAI, LLMs & Agentic Systems- Engaged in hands-on exploration and prototyping of LLM-based systems across prompt engineering, RAG, vector databases, fine-tuning (LoRA/QLoRA), and agentic workflows, with implementations such as NL-to-SQL and document QA pipelines using LangChain/LangGraph- Supported GenAI platform modernization through code walkthroughs, static analysis, and functional understanding of existing LLM pipelines.ML Systems, Performance & MLOps- Assisted in analyzing end-to-end ML and GenAI systems to identify latency issues, performance bottlenecks, and architectural inefficiencies- Performed debugging, profiling, and structured analysis of model-serving and orchestration components to inform performance-improvement recommendations- Worked with existing ML pipelines to understand deployment patterns, system constraints, and scalability considerations.Delivery & Collaboration- Prepared weekly technical updates and decks for internal teams, summarizing progress, findings, and next steps- Coordinated with stakeholders to understand legacy architectures, data flows, and modeling approaches during knowledge-transfer phases.

Education

• Guru Gobind Singh Indraprastha University

  Bachelor of Technology (B.Tech.), Computer Science

• Army Public School, Dhaula Kuan

  School, Junior High/Intermediate/Middle School Education and Teaching

• Indian Institute of Technology Hyderabad

  Master of Technology - MTech, Computer Science