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
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Current Experience

Cma cgm

2 roles

AI Engineer

Jul 2025Present · 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 2025Jul 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 2024Aug 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 2024Jan 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

Education

Siksha 'O'​ Anusandhan University

Bachelor of Technology - BTech — Computer Science

Nov 2021Jun 2025

Vikash The Concept School

High School Diploma — CBSE

May 2012Mar 2019

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