Job DescriptionRole Summary

NWe are hiring a hands-on Senior Data Scientist / AI Engineer to design and productionize AI capabilities for automated understanding and validation of complex 2D engineering drawings. The role combines Computer Vision, OCR/Document AI, multimodal LLMs, RAG/Graph-RAG, Knowledge Graphs and deterministic engineering rules.

NKey Responsibilities

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- Build AI pipelines to extract title blocks, notes, dimensions, tolerances, GD&T;, datums, callouts, tables, references and drawing views from PDF/DWG/DXF-derived engineering content.
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- Develop Computer Visionmodels for region detection, layout understanding, object detection, segmentation, symbol recognition, view classification and annotation localization.
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- Design OCR/document-processing pipelines for dense technical drawings using tools such as PaddleOCR, Docling, OpenCV, YOLO, Vision Transformers or equivalent frameworks.
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- Build multimodal/LLM workflows for engineering interpretation, structured extraction, contextual reasoning and JSON-based outputs with strong guardrails.
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- Develop RAG and Graph-RAG solutions over engineering standards, specifications, component rules and business-unit guidelines using vector search and Knowledge Graphs such as Neo4j.
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- Implement hybrid validation combining deterministic rule engines, symbolic checks and LLM reasoning;

ensure exact geometric/tolerance checks are not delegated solely to LLMs.

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- Create explainable review findings including violated rule, source/citation, confidence, rationale and recommended corrective action.
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- Design Human-in-the-Loop feedback mechanisms to capture accept/reject/edit/override decisions and improve models, prompts, retrieval and rules.
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nModel Evaluation &Productionization;

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- Define accuracy benchmarks and golden datasets;

track precision, recall, F1, IoU, OCR CER/WER, extraction accuracy, retrieval quality, validation accuracy and hallucination rate.

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- Perform failure analysis, prompt/model benchmarking, regression testing and continuous accuracy improvement.
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- Convert experiments into production-grade Python/FastAPI services;

containerize with Docker and support Kubernetes/GPU deployment.

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- Optimize inference latency, GPU memory and throughput for enterprise NVIDIA infrastructure such as H100/A100 or equivalent.
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- Implement MLOps practices for model/dataset/prompt versioning, experiment tracking, model registry, deployment pipelines and monitoring.
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nRequired TechnicalSkills

NArea

nExpected Capability

NProgramming

nPython, SQL;

robust software engineering practices

NComputer Vision

nOpenCV, YOLO/object detection, segmentation, layout understanding, image preprocessing

NOCR / Document AI

nPaddle OCR, Docling or equivalent;

table/text/technical-document extraction

NDeep Learning

nPyTorch and/or TensorFlow;





transfer learning and model evaluation

NGenAI / Multimodal

nLLMs, VLMs, prompt engineering, structured outputs, tool/function calling

NRAG / Graph-RAG

nEmbeddings, chunking, vector search, hybrid retrieval, reranking, query transformation

NKnowledge Graph

nNeo4j or equivalent graph DB;

graph modeling and graph retrieval

NLLM Optimization

nLoRA/QLoRA, PEFT, quantization, fine-tuning, context and inference optimization

NAI Engineering

nFastAPI/REST, Docker, Kubernetes, Git, GPU deployment

NMLOps

nMLflow or equivalent;

experiment/model lifecycle, monitoring and CI/CD integration

NPreferred Domain Experience

NStrong preference for candidates with experience in aerospace, mechanical/manufacturing, automotive, rail, CAD/PLM, engineering drawing automation or technical document intelligence. Exposure to GD&T;, ASME Y14.X, ISO GPS or equivalent drawing standards is highly desirable.

NEducation

nBachelor's or Master's degree in Computer Science, AI/ML, Data Science, Electronics, Mechanical Engineering, Mathematics, Statistics or a related discipline. Master's degree is preferred.

NCandidate Profile

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- Hands-on senior engineer who can code, train/evaluate models, troubleshoot accuracy issues and take AI components into production.
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- Able to work closely with engineering SMEs and convert standards/domain rules into machine-readable knowledge and validation logic.
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- Comfortable operating in secure enterprise environments with restricted internet access and on-premises model hosting.
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📌 Hiring: Senior Data Scientist (Karnataka)
🏢 Cyient
📍 Karnataka