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const developer = {
name: "Nikhil Koche",
title: "AI Engineer",
specialization: "GenAI & ML",
email: "nikhilkoche682@gmail.com",
location: "Canada",
experience: "5+ years"
}
# Navigation Menu
class
Portfolio:
# Social Links
social_links
= {
}
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# Professional Summary
class AIEngineer:
def __init__(self):
self.role = "AI & ML Engineer"
self.experience = "5+ years"
self.specialization = [
"Generative AI & LLM Applications",
"Cloud-native Development",
"Full-stack Solution Delivery"
]
def get_achievements(self):
return [
"Pioneered scalable LLM apps with LangChain, OpenAI, and Hugging Face",
"Cut deployment time by 40% and lowered infrastructure costs",
"Orchestrated systems supporting 1,000+ daily interactions",
"Resolved 95% of data issues through automated validation",
"Drove 15% efficiency boost and 20% reduction in manual errors"
]
# Professional Experience
class Experience:
def ai_ml_engineer_current(self):
company = "AI Hub, Durham College"
location = "Oshawa, Ontario"
duration = "Sept 2024 - Present"
responsibilities = [
"Led delivery of multiple AI projects with enterprise clients",
"Architected LLM-driven multi-agent systems and forecasting models",
"Deployed solutions on Azure and AWS infrastructure"
]
def ai_ml_engineer_projects(self):
duration = "Jul 2022 - Aug 2024"
focus = [
"Instagram Automation Tool - Borderscapes Immigration",
"AI for Scientific Literature - PhD Research Assistant",
"Vision-Based Inventory Management System",
"Business Intelligence Dashboard - Progetto Ecommerce"
]
def software_developer(self):
company = "ICEICO Technologies Pvt. Ltd"
location = "Nagpur, India"
duration = "Nov 2020 - Jun 2022"
achievements = [
"Migrated MEAN stack system to Ironclad, improving efficiency by 25%",
"Accelerated deployment speed by 40% through microservices transition"
]
# Featured Projects
class Projects:
project = {
name: "Multi-Agent KPI Insights Platform",
tech: ["LangChain", "SQL", "Power BI"],
description: "LLM-powered system automating KPI identification from enterprise databases",
impact: "70% reduction in manual analysis time",
status: "Production"
}
project = {
name: "AI News Platform - TorontoToday",
tech: ["Python", "NLP", "Multi-source APIs"],
description: "Conversational assistant for city news summarization",
impact: "60% decrease in research time",
status: "Production"
}
project = {
name: "Volumetric Food Estimation",
tech: ["Computer Vision", "CNN", "Deep Learning"],
description: "Deep learning model for food volume prediction from images",
impact: "90% prediction accuracy on 1,000+ samples",
status: "Research"
}
project = {
name: "Instagram Automation Tool",
tech: ["Python", "Graph API", "OpenAI GPT-4o"],
description: "AI chatbot for automated Instagram conversations",
impact: "1,000+ daily interactions, 60% time reduction",
status: "Production"
}
project = {
name: "AI Scientific Literature Q&A",
tech: ["LangChain", "FastAPI", "PineconeDB"],
description: "Document-driven Q&A tool for PhD research",
impact: "95% accuracy, 70% reduction in manual scanning",
status: "Production"
}
project = {
name: "Vision-Based Inventory Management",
tech: ["YOLOv8", "Vertex AI", "SingleStore"],
description: "Intelligent inventory tracking using object detection",
impact: "95% accuracy, 50% efficiency improvement",
status: "Production"
}
# Technical Skills & Expertise
class Skills:
# GenAI & LLM Tools
genai_tools = [
"Prompt Engineering", "Chain-of-Thought Reasoning", "Zero-shot/Few-shot Learning",
"LangChain", "OpenAI (GPT-4/4o)", "Hugging Face Transformers",
"RAG", "Vector Databases (Pinecone, FAISS, Qdrant)",
"Open-Source LLMs (LLaMA, Mistral, Qwen)", "LLM Fine-Tuning"
]
# Machine Learning & AI
ml_ai = [
"Deep Learning", "NLP", "Computer Vision", "Object Detection (YOLOv8)",
"TensorFlow", "PyTorch", "Scikit-learn", "XGBoost", "LightGBM",
"OCR (Tesseract, PaddleOCR)", "MLflow", "Vertex AI"
]
# Cloud & DevOps
cloud_devops = [
"AWS (EC2, Lambda, S3, DynamoDB, RDS, CloudWatch)",
"Azure (Azure ML, Cognitive Services)", "GCP (Vertex AI)",
"Docker", "Kubernetes", "Terraform", "CI/CD (GitHub Actions)"
]
# Software Engineering
software_engineering = [
"Python", "JavaScript", "C/C++", "HTML5", "CSS3", "React", "TypeScript",
"RESTful APIs", "GraphQL", "Flask", "FastAPI", "Microservices"
]
# Data Engineering & Databases
data_engineering = [
"PostgreSQL", "MySQL", "MongoDB", "DynamoDB",
"ETL/ELT Workflows", "Apache Kafka", "Amazon Kinesis",
"Amazon S3", "Amazon Redshift", "AWS Glue", "Amazon Athena"
]
# BI & Visualization
bi_visualization = [
"Power BI", "Tableau", "DAX", "Power Query",
"KPI Dashboards", "Interactive Visual Analytics", "Report Automation"
]
# Education
class Education:
def post_graduation(self):
degree = "Post Graduation in Data Analytics and AI"
specialization = "Design and Implementation"
institution = "Durham College, Ontario, Canada"
def bachelor_degree(self):
degree = "Bachelor of Engineering"
specialization = "Computer Technology"
institution = "RTMNU University, India"
# Certifications
class Certifications:
certifications = [
"AWS Certified Cloud Practitioner",
"Red Hat Certified System Administrator (RHCSA)"
]
# Contact Information
class Contact:
def get_contact_info(self):
return {
email: "nikhilkoche682@gmail.com",
phone: "905-782-9278",
location: "Canada",
specialization: "AI Engineer | Data Engineer | AI & ML | AI-OPS"
}
# Let's Connect!

Passionate about AI/ML innovation and always interested in discussing cutting-edge projects and opportunities in Generative AI, LLMOps, and cloud-native solutions.