About
Hello! I’m Manabendra Rout, a seasoned Machine Learning Research Engineer with a passion for pushing the
boundaries of AI technology. With over 8 years of experience in data science and machine learning, I
specialize in developing cutting-edge solutions in Generative AI, natural language processing (NLP), and
large language model (LLM) fine-tuning. My expertise lies in building scalable AI systems, fine-tuning
models for domain-specific applications, and optimizing inference for real-world use cases.
Beyond
technical implementation, I take pride in my role as a mentor and collaborator, guiding junior team members,
leading design discussions, and ensuring high-quality deliverables through thorough code reviews. I thrive
at the intersection of research and practical application, transforming complex ideas into impactful
solutions.
Feel free to explore my portfolio to learn more about my projects and contributions to the
field of AI.
Machine Learning Researcher
I am a self-taught programmer and Senior Applied AI Engineer currently working with sirion.ai on a Contract Lifecycle Management (CLM) product. I have worked on multiple Generative AI, NLP and Computer Vision microservices for incorporating various features to the product.
- Birthday: 1 August 1994
- Website: mrout94.github.io
- Phone: +91-7757088502
- Email: manabendrarout@gmail.com
- City: Bengaluru, India
- Age: 30
- Degree: Bachelors
- Alma Mater: NIT Rourkela
- Open to Roles: Applied AI Engineer, Data Scientist
I specialize in developing Generative AI applications, Natural Language Processing (NLP), and fine-tuning Large Language Models (LLMs), with expertise in Python and frameworks like PyTorch. My work spans scalable model deployment, optimization, and monitoring to ensure robust real-world applications. I believe a strong foundation in mathematics, programming, and problem-solving is essential for success in the rapidly evolving AI landscape.
Resume
A methodical and experienced AI Engineer with expertise in Deep Learning, Generative AI, and NLP. Passionate about creating innovative solutions and advancing the field of artificial intelligence.
Summary
Manabendra Rout
Innovative and detail-oriented AI Engineer with 8+ years of experience in developing, fine-tuning, and deploying Generative AI and NLP solutions. Proficient in managing the complete lifecycle of AI projects, including data generation, model training, optimization, inferencing, and scalable deployment for real-world applications.
- Bengaluru, Karnataka, India
- (+91) 7757088502
- manabendrarout@gmail.com
Education
B.Tech in Mechanical Engineering
2012 - 2016
National Institute of Technology (NIT), Rourkela, India
Internship
Academic Intern
May 2015 - July 2015
Tata Motors, Jamshedpur, India
Achieved a significant reduction in torque variation of truck engines by developing an anomaly detection algorithm to preemptively identify defective engines and trace problematic parameters to their sources. Utilized statistical techniques and Isolation Forest.
Professional Experience
Applied AI Engineer
Feb, 2022 - Present
Sirion, Bengaluru, India
- Created a RAG-based chatbot utilizing open-source LLMs to support advanced contract Q&A.
- Fine-tuned multiple open-source LLMs (e.g., Llama3, Llama2, Qwen, MPT) for legal domain tasks such as instruction-following and conversational Q&A using distributed training methods (FSDP, DDP).
- Fine-tuned multiple text embedding models using contrastive learning techniques and designed novel data generation approaches for domain-specific embeddings, improving downstream task performance.
- Contributed to development of a Auto Redlining Application using GPT-4o for automating contract modification/negotiations in alignment with organizational guidelines.
Data Scientist
Sep, 2020 - Feb, 2022
United Health Group, Noida, India
- Applied NLP techniques for topic modeling of customer feedback, enabling actionable insights to reduce cancellations by 17%.
- Delivered a predictive modeling system achieving an F1 score of 0.82 for forecasting order outcomes.
Assistant Manager
Jul 2016 - Sep 2020
Bajaj Auto Limited, Pune, India
- Developed a GBM-based model to predict bearing friction loss, reducing analysis time by 12%.
- Designed a web-based framework for automating test data handling, achieving 90% time savings.
- Applied ML techniques to address material strength predictions and dynamic component behavior.
Projects
Actions speak louder than words. As I am not at liberty to share the projects I have done professionally due to organizational non-disclosure agreements, however I can share some of the hobby/hackathon projects I have undertaken in my own time.
- All
- Structural Data
- Computer Vision
- NLP
Certifications
I have completed several courses on Deep Learning, Computer Vision and NLP on my quest to better understand the technology. Below are the credentials for some MOOCs I have completed successfully.
Neural Networks and Deep Learning - Coursera
Completed Coursera's "Neural Networks and Deep Learning" course whilst completing all the coding
assignments with 100% grade.
This course covers majority of the foundational concept of neural
networks and deep learning including intuition and basic mathematics.
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
Completed Coursera's "Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and
Optimization" course whilst completing all the coding assignments with 99.2% grade.
This course tries to open the deep learning black box to understand the processes that drive performance
and generate good results systematically.
Structuring Machine Learning Projects
Completed Coursera's "Structuring Machine Learning Projects" course whilst completing all the coding
assignments with 100% grade.
This course teaches how to diagnose errors in a machine learning system; prioritize strategies for
reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to
and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and
multi-task learning.
Convolutional Neural Networks
Completed Coursera's "Convolutional Neural Networks" course whilst completing all the coding assignments
with 99.45% grade.
This course teaches how to build a convolutional neural network, including recent variations such as
residual networks; apply convolutional networks to visual detection and recognition tasks; and use
neural style transfer to generate art and apply these algorithms to a variety of image, video, and other
2D or 3D data.
Sequence Models
Completed Coursera's "Sequence Models" course whilst completing all the coding assignments with
100% grade.
This course teaches how to build and train Recurrent Neural Networks (RNNs) and commonly-used variants
such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural
language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve
different NLP tasks such as NER and Question Answering.
