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Shardul Manohar

Shardul Manohar

I am an AIML engineer with experience in computer vision, data science and RAG, with a very strong background in mathematics, statistics and physics.

Talent
PuneMember since March 23, 2026
Machine Learning & Deep Learning SystemsComputer Vision & Image UnderstandingObject DetectionLLMs, Vector Embeddings & RAGStatistical Modelling & Feature EngineeringLinear/Logistic RegressionDecision Trees, Random ForestKNN, SVM, Naive BayesModel Training, Evaluation & OptimizationProduction ML Pipelines & APIsScientific & Applied ComputingPythonC++JavaNumPyPandasMatplotlibSQLMongoDBTensorFlowKerasScikit-learnCNNsU-NetLSTMTransfer LearningYOLOEfficientNetspaCyNamed Entity Recognition (NER)Sentiment AnalysisVector EmbeddingsFAISSRetrieval-Augmented Generation (RAG)OpenCVImage SegmentationOCRDocument Image AnalysisREST APIsGitJupyterRPA Integration
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Machine Learning & Deep Learning SystemsComputer Vision & Image UnderstandingObject DetectionLLMs, Vector Embeddings & RAGStatistical Modelling & Feature Engineering

About

AI/ML Engineer with 3+ years of experience building, training, and deploying machine learning and deep learning systems across industrial and research environments. Strong hands-on expertise in computer vision, predictive modeling, vector embeddings, and LLM-based systems, with experience integrating models into production workflows. Comfortable working across the full ML lifecycle—from data preparation and experimentation to deployment, monitoring, and iteration.

Experience

AI/ML Engineer at Optra Scan Pvt Ltd (2025-07 – Present)

Built and trained deep learning models for disease diagnosis from cytology slides and Tuberculous bacilli detection in medical imaging.

  • Built and trained deep learning models for disease diagnosis from cytology slides, and Tuberculous bacilli detection.
  • Applied CNN-based architectures (YOLO, EfficientNet, custom Keras models) for medical image analysis.
  • Developed end-to-end computer vision pipelines for digital pathology, from preprocessing to inference.
  • Collaborated with domain experts to refine data labeling, evaluation metrics, and model performance.

AI/ML Engineer at Demos Foundation centre for Research in Humanities (2025-02 – 2025-07)

Designed and implemented vector embedding pipelines, similarity search systems, and RAG-based document understanding solutions.

  • Designed and implemented vector embedding pipelines for large-scale document and image datasets.
  • Built similarity search and duplicate detection systems using FAISS.
  • Developed RAG-based systems for document understanding and semantic retrieval.
  • Implemented OCR, NER, and sentiment analysis pipelines using spaCy and related NLP tooling.

Software Engineer at AutomationEdge (2022-11 – 2025-01)

Developed ML-powered components within an enterprise automation platform, including deep learning pipelines and clustering algorithms.

  • Developed ML-powered components within an enterprise automation platform.
  • Designed a deep learning pipeline for image-based table extraction from documents.
  • Implemented a novel Best-K selection algorithm for K-Means clustering, improving clustering stability.
  • Integrated ML models into production RPA workflows via APIs and automation logic.
  • Contributed to GenAI initiatives, including LLM-assisted code generation and model refinement.

Education

BS–MS in Dual Degree in Science – IISER-Pune (2023)

Skills

data science and RAGwith a very strong background in mathematicsstatistics and physics.

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