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Dynamic and results-oriented AI/ML Architect with over 15+ years of progressive experience in designing, implementing, and optimizing cutting-edge artificial intelligence and machine learning solutions. Adept at leading cross-functional teams and collaborating with stakeholders to translate business requirements into scalable and innovative AI-driven products. Demonstrated expertise in architecting end-to-end AI/ML pipelines, leveraging a comprehensive understanding of algorithms, frameworks, and cloud technologies. Proven track record of delivering high-impact projects across diverse domains, including natural language processing, computer vision, predictive analytics, and recommendation systems. Skilled in driving organizational transformation through the adoption of AI/ML technologies, promoting a culture of continuous learning and innovation. Strong leadership, communication, and problem-solving skills, with a passion for driving business value through data-driven insights and intelligent automation.

Dynamic AI/ML Engineer with a proven track record at Publicis Groupe, enhancing text classification with transformer-based NLP models and streamlining AI deployment. Excelled in collaborative projects, leveraging expertise in Python programming and distributed computing. Demonstrated exceptional problem-solving skills and a knack for innovative algorithm development, significantly boosting decision-making processes.

Data Scientist and AI Engineer skilled in machine learning, NLP, data analytics, Gen AI seeking to apply technical expertise in AI-driven problem solving and automation to deliver impactful business outcomes within a forward-thinking organization.


  Results-driven AI/ML Developer and Python Developer with over 10 years of experience in designing, developing, and deploying enterprise-grade AI/ML, data engineering, and cloud-based applications across manufacturing, finance, healthcare, and retail domains.
  Applied prompt engineering, dynamic chaining, and agent-based architectures using LangChain to enhance response accuracy and explainability.
  Proficient in integrating LLMs (OpenAI, Hugging Face) into production using FastAPI and Flask, with hands-on experience in MLOps, CI/CD, and model monitoring.
  Experienced AI/ML Developer skilled in building, training, and deploying machine learning and deep learning models using Python, PyTorch, TensorFlow, and AWS.
  Experienced in designing and deploying NLP pipelines for sentiment analysis, document summarization, named entity recognition (NER), and translation using Hugging Face Transformers, spaCy, and GPT-based architectures.
  Hands-on experience in computer vision, building and deploying object detection, OCR, and image segmentation solutions using OpenCV, TensorFlow, and Keras for real-time visual inference.
  Highly skilled in Python development for data manipulation, transformation, and analytics using Pandas, NumPy, Scikit-learn, PySpark, and Matplotlib, with proven success in building scalable ETL pipelines on Azure Databricks and AWS Glue to process multi-terabyte datasets via batch and streaming ingestion.
  Experienced in developing and deploying GenAI and machine learning solutions, including LLMs, Retrieval-Augmented Generation (RAG), LangChain orchestration, and Hugging Face Transformer fine-tuning, to deliver predictive intelligence and automate business workflows.
  Strong expertise in Delta Lake architecture (bronze–silver–gold) for ACID transactions, schema evolution, and query optimization, as well as in metadata-driven, incremental data pipelines integrating structured and unstructured data from diverse sources into Azure Data Lake Gen2, Synapse Analytics, Redshift, and HDFS.
  Demonstrated ability to optimize Spark performance through partitioning, caching, and adaptive query execution, achieving up to 60% improvement in compute efficiency, and faster SLA adherence.
  Proficient in implementing CI/CD pipelines using Azure DevOps, Jenkins, Terraform, Docker, and Kubernetes, and in establishing data validation frameworks with PySpark and Great Expectations to ensure data accuracy and integrity.
  Extensive experience leveraging Azure (ADF, Synapse, Event Hubs, Purview, Delta Live Tables), and AWS (S3, EMR, Redshift, Kinesis, Lambda, CloudFormation, CloudWatch) for secure, compliant, and cost-optimized data ecosystems.
  Skilled in using AI-assisted development tools, such as GitHub Copilot, for intelligent code generation, testing, and documentation, enhancing development efficiency and quality assurance.
  Experienced in performing advanced analytics and visualization with Power BI, Tableau, and Excel (DAX, SQL) to deliver actionable business insights and KPI dashboards for stakeholders. Recognized for strong collaboration with cross-functional ML, DevOps, and product teams in Agile/Scrum environments, leading cloud migration, data governance, and compliance initiatives (GDPR, PII masking) to build reliable, scalable, and insight-driven enterprise data solutions.


Overall, 5+ years of experience in Data Science and Big Data in the Business Industry with adept knowledge of Data Analytics, Machine Learning (ML), and Predictive Modeling. Machine Learning and Computer Vision expert with experience in image processing and analysis. Proven track record in developing and optimizing computer vision algorithms and ML models. Skilled in refining ML models to improve accuracy and collaborating with cross-functional teams to integrate AI/ML features into applications. Specialized in Text Analytics, developing Statistical Machine Learning and Data Mining solutions using R, Python, and Tableau. Proficient in Data Analytics, including Data Reporting, Ad-hoc Reporting, and OLAP reporting. Strong command over SQL, with experience in RDBMS (e.g., MySQL) and NoSQL databases (e.g., MongoDB). Skilled in using Spark MLlib utilities for machine learning tasks and various visualization tools like Tableau, SAS, QlikView, and Microsoft BI. Expertise in operations research techniques, mathematical programming, heuristic algorithms, and stochastic modeling. Hands-on experience in designing optimization models using Python and relevant packages such as PuLP, PYOMO, and CVXPY, with proficiency in CPLEX. Well-versed in TR components and NESS requirements into scalable analytical models, working with Hadoop ecosystem components, and designing captivating visualizations using Tableau. Knowledgeable in various machine learning algorithms and techniques, including Reinforcement Learning, LDA, Naive Bayes, Random Forests, Decision Trees, Linear and Logistic Regression, SVM, Clustering, and neural networks.

Charishma Polineni

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AI/ML Engineer

Machine Learning Intern

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Master of Science - Computer Science

Bachelor of Technology - Computer Science

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AI/ML Engineer

Machine Learning Intern

Master of Science - Computer Science

Bachelor of Technology - Computer Science

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