Omkar Pattnaik

AI Researcher

Bengaluru, Karnataka, India0 mo experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in AI/ML solutions for logistics.
Proven track record in cross-functional collaboration.
Strong background in MLOps and production deployment.

Stackforce AI infers this person is a SaaS-focused AI Engineer with expertise in logistics and data engineering.

Contact

Skills

Core Skills

Ai EngineeringMlopsData EngineeringData ScienceMachine Learning

Other Skills

AI model developmentAI-driven solutionsAmazon Web Services (AWS)Apache AirflowCalculusCascading Style Sheets (CSS)CommunicationComputer NetworkingData AnalysisData StructuresDatabase Management System (DBMS)Deep LearningDevOpsDjangoDocker

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Cma cgm

2 roles

AI Engineer

Jul 2025 – Present · 11 mos

Contributed to the ERA Program, a major technology initiative leveraging AI and automation to transform Global Business Services (GBS) operations across multiple countries (India, China, Costa Rica, Tallinn, Lebanon).
Designed, developed, and implemented AI-driven solutions to streamline and automate complex business processes, resulting in improved operational efficiency and enhanced customer experience.
Collaborated with cross-functional teams to eliminate process waste, re-engineer workflows, and deploy intelligent automation for tasks like booking, document processing, shipping operations, and financial workflows.
Worked on creating AI models and automation pipelines to reduce manual effort, improve accuracy, and enable scalability for over 7,700 users across 60+ business processes.
Supported the roadmap for AI initiatives prioritizing key operational tasks, customer service improvements, and finance automation using progressive AI technologies.
Monitored and optimized AI system performance, ensuring seamless integration with business functions and driving measurable time savings and capacity improvements within CMA CGM operations.

AI-driven solutionsautomationcross-functional collaborationAI model developmentperformance optimizationAI Engineering+1

AI Engineer Intern

Jan 2025 – Jul 2025 · 6 mos

AI Model Development & Optimization
Develop and fine-tune OCR-based AI models for extracting structured and unstructured data from invoices.
Implement NLP models for entity recognition, data validation, and document classification.
Optimize machine learning pipelines for high accuracy, scalability, and real-time processing.
Data Engineering & Preprocessing
Work with large volumes of invoice and financial data, ensuring cleaning, normalization, and structuring for AI model training.
Design data pipelines for continuous ingestion and processing of invoice documents.
Handle document variations across vendors, formats, and languages.
Automation & Integration
Integrate AI models with existing ERP and accounting systems to enable seamless invoice validation and approval workflows.
Develop APIs & microservices for scalable and efficient AI-powered invoice processing.
Automate discrepancy detection in invoices, flagging anomalies for human review.
Deployment & Monitoring
Deploy AI models in cloud or on-premises environments using platforms like Google Cloud Vertex AI
Implement MLOps best practices for continuous monitoring, retraining, and improving model performance.
Track KPIs such as processing time, accuracy, and error rates to optimize the AI agent.
Collaboration & Stakeholder Communication
Work closely with finance, accounts payable, and IT teams to align AI-driven automation with business needs.
Conduct proof-of-concept (PoC) studies and present findings to stakeholders.
Ensure compliance with data privacy and financial regulations in AI implementations.

OCR-based AI modelsNLP modelsdata engineeringcloud deploymentAI EngineeringData Engineering

Pw (physicswallah)

Data Scientist Intern

May 2024 – Aug 2024 · 3 mos · Remote

Developed and deployed machine learning models to enhance learning management system (LMS) functionalities, improving user engagement and personalization.
Worked on data preprocessing, feature engineering, and implementing algorithms for predictive analytics and recommendation systems.
Collaborated with cross-functional teams to integrate ML models into production, ensuring scalability and performance optimization.
Gained hands-on experience in deep learning, model tuning, and cloud-based deployment for real-time student interaction insights.
Utilized technologies like Python, TensorFlow, and cloud services for building scalable ML pipelines.

machine learning modelsdata preprocessingpredictive analyticsData ScienceMachine Learning

Github

Machine Learning Open Source Contributor

Jan 2024 – Jan 2024 · 0 mo · Remote

Contributed to Machine learning Projects of Krish Naik, My contribution was primarily on retail based projects that involved regression and classification models in order to decrease the churn rate of a retail company.
Thought Process:
Step1: Ensured the company is profitable 📈 by reducing the operations cost
Step2:Made sure to reduce the churn rate by analyzing company's loyal users and offering them offers and discounts using clustering.
Step3: Analyzing customer behaviour and sentiment analysis for predicting their next purchase item using multiple regression.

regression modelsclassification modelscustomer behavior analysisMachine Learning