Contact-
www.linkedin.com/in/snehasishrayaguru- (LinkedIn)
Top Skills
Model Training
Computer Vision
Large Language Models (LLM)
Certifications
Building LLM Applications With
Prompt Engineering
Snehasish Rayaguru
AI and ML ENGINEER- @Squbix Digital
Bhubaneswar, Odisha, India
Summary
I am Snehasish Rayaguru, an AI/ML Engineer with expertise in
large language models, retrieval-augmented generation systems,
and intelligent automation solutions. Currently pursuing my M.Tech
in Computer Science Engineering, I specialize in developing
conversational AI, OCR systems, and predictive analytics models
that drive real-world impact across healthcare, finance, and
agricultural sectors.
With a B.Tech in Computer Science (AI & ML) from Trident
Academy of Technology and hands-on experience across multiple
organizations, I have successfully engineered end-to-end machine
learning solutions from concept to deployment. My technical
expertise spans Python, TensorFlow, PyTorch, and advanced NLP
frameworks including LangChain and RAG architectures.
In my current role as AI/ML Engineer at Squbix Digital, I focus
on fine-tuning large language models for healthcare applications
and developing computer vision solutions for automated pattern
detection. Previously, I contributed to AI model optimization at Outlier
and built high-accuracy predictive models at Divine AI, achieving
98% accuracy in time series forecasting and 99% precision in
healthcare diagnostics.
My project portfolio demonstrates versatility across domains:
GitaGPT (contextual NLP chatbot), UDYAN (crop price forecasting
using ARIMA), and Diabetics Sentinel (precision diagnostic
modeling). I've also developed full-stack applications including
"Bcakbook" (social platform using Flutter) and "Krushi" (multilingual
agricultural guidance platform supporting Hindi, English, and Odia).
What drives me is the intersection of cutting-edge AI research
and practical problem-solving. I excel at translating complex data
patterns into actionable business insights and building scalable AI
systems that enhance decision-making processes. My approach
combines rigorous technical methodology with clear communication
to bridge the gap between advanced AI capabilities and business
objectives.
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As I continue advancing in the AI/ML field, I'm passionate about
leveraging emerging technologies like generative AI, computer
vision, and cloud-native architectures to create innovative
solutions that address real-world challenges and drive meaningful
technological progress.
Experience
Squbix Digital
AI Engineer
November 2024 - Present (1 year)
Bhubaneswar, Odisha, India
As an AI/ML Engineer at Squbix Digital, I specialize in engineering and
fine-tuning large language models for healthcare sector applications
while developing advanced OCR systems for document processing and
implementing computer vision solutions for automated pattern detection. My
role involves applying machine learning techniques for predictive analytics
in healthcare domains and working collaboratively with cross-functional
teams to deliver scalable AI solutions that drive measurable business
outcomes. I leverage cutting-edge technologies including LLM fine-tuning,
retrieval-augmented generation systems, and deep learning frameworks to
solve complex real-world challenges, focusing on advancing healthcare AI
capabilities, optimizing model performance for production environments, and
contributing to innovative projects that enhance digital transformation initiatives
across the organization.
Outlier
AI Training Coding Expert
October 2024 - November 2024 (2 months)
India
As part of the dynamic team at Outlier AI, I contribute to harnessing the power
of artificial intelligence and machine learning to uncover valuable insights from
complex data. Outlier AI's platform empowers businesses to make data-driven
decisions by identifying trends, patterns, and outliers that would otherwise go
unnoticed. We work across multiple industries, helping companies optimize
performance, manage risks, and unlock growth opportunities. Through my role,
I am passionate about driving innovation and transforming how organizations
leverage data for strategic advantage.
Mentorness
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3 months
Artificial Intelligence Developer
July 2024 - August 2024 (2 months)
During my internship at Mentorness, I had the chance to work on innovative
machine learning projects that significantly enhanced my technical skills and
practical experience.
One of the standout projects was Skin Disease Prediction, where I developed
a model to diagnose various skin conditions from images. This project involved
using computer vision techniques and deep learning algorithms to analyze skin
images and predict potential skin diseases. I focused on data preprocessing,
model training, and performance evaluation to ensure accurate and reliable
predictions.
Another exciting project was GitGPT, where I contributed to developing
an advanced conversational AI system. This project aimed to create a
chatbot capable of generating human-like responses and engaging in
meaningful conversations. I worked on integrating natural language processing
techniques, fine-tuning language models, and enhancing the chatbot’s ability
to understand and respond to user queries effectively.
Through these projects, I gained hands-on experience with tools such as
Python, TensorFlow, Keras, and NLP libraries, while also deepening my
understanding of machine learning and AI applications.
Machine Learning Intern
June 2024 - July 2024 (2 months)
During my internship at Mentorness, I worked on several impactful machine
learning projects that enhanced my technical skills and provided valuable
insights into predictive modeling.
One of the key projects I tackled was **Salary Prediction**, where I used
regression techniques to forecast employee salaries based on various factors
such as experience, education, and job role. This project involved extensive
data preprocessing, feature engineering, and model evaluation to achieve high
accuracy.
Another significant project was **Credit Card Approval Prediction**, where
I developed a model to assess whether it's appropriate to approve a credit
card application for a potential customer. This involved building a classification
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model that analyzed factors such as credit history, income, and other financial
indicators to predict the likelihood of responsible credit usage. Working with
imbalanced datasets, tuning model parameters, and ensuring prediction
reliability were key challenges I successfully navigated.
Through these projects, I gained hands-on experience with tools and libraries
such as Python, Pandas, Scikit-learn, and Matplotlib, while deepening my
understanding of the end-to-end machine learning pipeline—from data
preparation to model deployment.
DivineAI Pvt Limited
Ex Data Science Developer
July 2022 - November 2022 (5 months)
bhubaneswar
As a Data Scientist at Divine Ai Pvt. Ltd., I worked on impactful projects like
UDYAN (Crop Price Prediction) and Diabetics Sentinel-Precision Detection.
These experiences have honed my skills in Python, data manipulation,
data visualization, and various machine learning techniques. I am proficient
in utilizing tools such as Pandas, NumPy, and Jupyter, and I am adept at
identifying and troubleshooting complex problems.
Education
Trident Academy of Technology (TAT), Bhubaneswar
Bachelor of Technology - BTech, Artificial Intelligence · (December 2020 - May
2024)
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