Kiran Kumar (Kumar) Kanathala-Applied NLP: Word-Level Encoding for Smarter Event Predictions
Check rate
Experience
Applied NLP: Word-Level Encoding for Smarter Event Predictions
University of Siegen
- Engineered 12+ Seq2Seq models (LSTMs/GRUs) to train an AI model, supporting AI Agent Evaluation Analyst and online projects in complex systems.
- Conducted 15+ experiments to improve forecasting accuracy by 28%, applying analytical thinking and testing models for QA and edge case coverage.
- Researched 20+ papers as a consultant to guide Large Language Model design, ensuring logical implications and domain of expertise alignment.
- Saved 40% compute time via model compression with reusable PyTorch framework, aiding developers and writers to suggest refinements and improve policies.
Generative AI Applications with RAG and LangChain
IBM & Coursera
- Built a Large Language Model Q&A bot using LangChain, enhancing retrieval efficiency by 35% for online projects in my domain of expertise.
- Applied prompt engineering to train an AI model, improving response accuracy by 25%, reducing irrelevant outputs by 30%, supporting AI Agent Evaluation Analyst tasks.
AI Engineer (Master Thesis)
ABB AG Research Center
- Designed and deployed 32+ self-supervised models to train an AI model using Python and TensorFlow for AI Agent Evaluation Analyst tasks in complex systems.
- Built and managed Azure ML data pipelines supporting 3 teams, enabling QA and developers to review evaluation tasks and improve edge case coverage.
- Developed pretext tasks for 100K+ samples, annotating cause-effect relationships to enhance Large Language Model accuracy and reduce manual labeling by 70%.
- Delivered strong business outcomes by applying analytical thinking and logical implications to define clear expected behaviors and gold standards in diagnostics.
Full Stack Developer
ABB AG Research Center
- Built full-stack tools using Python, JavaScript, React to train an AI model, integrating 10+ datasets/APIs for AI Agent Evaluation Analyst tasks.
- Collaborated in 10-person team as consultant, improving workflows, reducing errors by 20%, ensuring QA and edge case coverage in complex systems.
- Delivered 10+ online projects under deadlines, reviewing evaluation tasks, identifying inconsistencies, and supporting 4+ monthly stakeholder decisions in domain of expertise.
- Developed web app integrating 4+ renewables, annotating cause-effect relationships, enhancing client energy use by 35%, and defining clear expected behaviors for policies.
AI-Powered Resume and Cover Letter Tailoring Website
- Developed a web app with Large Language Models, LangChain, RAG, Pinecone for AI Agent Evaluation Analyst tasks, improving online projects in the domain of expertise.
- Built and deployed AI model system with cloud pipelines, enhancing QA, annotating cause-effect relationships, and supporting full-time opportunities.
Personal AI Chatbot portfolio
- Built an interactive chatbot portfolio using Large Language Models, React, Flask, Tailwind, RAG, chromaDB, enhancing AI Agent Evaluation Analyst capabilities and recruiter engagement by 60%.
- Integrated Git, Docker, CI/CD pipelines for QA, enabling training an AI model, improving edge case coverage and cutting recruiter review time by 40%.
Industry experience
See where this freelancer has spent most of their professional time.
Experienced in Information Technology, Education, Manufacturing, and Energy.
Business area experience
See which departments and functions this freelancer has contributed to most.
Experienced in Information Technology, Research and Development, Quality Assurance, and Product Development.
Summary
AI Agent Evaluation Analyst with expertise in training Large Language Models (LLMs), reviewing evaluation tasks for logic, completeness, and realism, identifying inconsistencies, defining gold standards, annotating reasoning paths, and applying analytical thinking to complex systems and policies.
- Analytical Thinking: Engineered 12+ Seq2Seq models, influencing 3+ teams and 2 theses, boosting forecasting accuracy by 28%.
- Attention to Detail: Reviewed evaluation tasks and scenarios for LLM logic, realism, and completeness, identifying inconsistencies and missing assumptions.
- Familiarity with Structured Data Formats: Built and deployed AI resume systems with cloud pipelines and prompt design, cutting tailoring time by 50%.
Skills
- Programming: Python, C/C++.
- Ai & Machine Learning: Pytorch, Tensorflow, Llms, Prompt Engineering, Ai-Generated Content Evaluation.
- Full Stack Development: Html, Css, Javascript, React.Js.
- Cloud & Infrastructure: Aws, Gcp, Azure, Docker, Kubernetes.
- Modelling & Simulation: Matlab/Simulink, Ansys, Autocad, Catia, Solidworks, Scenario Design, Policy Evaluation, Logic Puzzles.
- Large Language Model, Llm, Ai Model Training, Evaluation Tasks, Logic Puzzles, Structured Scenario Design, Json, Yaml, Prompt Engineering, Ai-Generated Content, Qa, Test-Case Thinking, Analytical Thinking, Policy Evaluation
Languages
Education
MLR Institute of Technology, JNTUH
Bachelor of Technology, Mechanical Engineering · Mechanical Engineering · Hyderabad, India
University of Siegen
Master of Science, Mechatronics with Specialization in AI · Mechatronics with Specialization in AI · Siegen, Germany
Certifications & licenses
The Systems Modeling Language (SysML®) v1.6
Udemy
AWS Cloud Technical Essentials
AWS & Coursera
Generative AI Engineering with LLMs Specialization
IBM & Coursera
Building Deep Learning Models with TensorFlow
IBM & Coursera
Deep Neural Networks with PyTorch
IBM & Coursera
Introduction to Machine Learning by Andrew Ng
Stanford Online & Coursera
IBM Certified Generative AI Specialist
Statistics
Experience
Global experience
Expertise
Qualifications
Profile
Frequently asked questions
Have questions? Find more information here.
Kiran Kumar is based in Siegen, Germany.
Kiran Kumar speaks the following languages: Hindi (Native), Telugu (Native), English (Advanced), German (Intermediate).
Kiran Kumar has at least 2 years of experience. During this time, Kiran Kumar has worked in at least 4 different roles and for 3 different companies. The average length of individual experience is 1 year and 6 months. Note that Kiran Kumar may not have shared all experience and actually has more experience.
Based on recent experience, Kiran Kumar would be well-suited for roles such as: Applied NLP: Word-Level Encoding for Smarter Event Predictions, Generative AI Applications with RAG and LangChain, AI Engineer (Master Thesis).
Kiran Kumar's most recent position is Applied NLP: Word-Level Encoding for Smarter Event Predictions at University of Siegen.
In recent years, Kiran Kumar has worked for University of Siegen, IBM & Coursera, and ABB AG Research Center.
Kiran Kumar is most experienced in industries like Information Technology, Education, and Energy. Kiran Kumar also has some experience in Manufacturing.
Kiran Kumar is most experienced in business areas like Information Technology, Research and Development, and Quality Assurance. Kiran Kumar also has some experience in Product Development.
Kiran Kumar holds a Master in Mechatronics with Specialization in AI from University of Siegen and a Bachelor in Mechanical Engineering from MLR Institute of Technology, JNTUH.
Kiran Kumar has 7 certificates. Among them, these include: The Systems Modeling Language (SysML®) v1.6, AWS Cloud Technical Essentials, and Generative AI Engineering with LLMs Specialization.
The availability of Kiran Kumar needs to be confirmed.
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Calculated based on our freelancers’ daily rates as of 6 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
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