Engineer - AI (Mining Automation)

WSP
Noida, Mumbai
Full timeFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Collaboration","Communication","Problem-solving"]

Develop and deploy AI-enabled automation for mining engineering and operational workflows. Build intelligent data extraction pipelines from mining reports and documents using OCR, layout understanding, multimodal models, and LLM techniques, with traceable, validated outputs. Create and evaluate machine learning solutions for predictive analytics, anomaly detection, and risk assessment, and contribute to graph-based knowledge and GraphRAG retrieval. Integrate solutions using Microsoft Azure AI services and collaborate with multidisciplinary teams on global mining projects.

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FursaFursa
WSP
WSP
2 days ago

Engineer - AI (Mining Automation)

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Source: Company careers pageValidated by: Fursa AI
Last checked: 3 hours agoStatus: Live

Job Summary

Develop and deploy AI-enabled automation for mining engineering and operational workflows. Build intelligent data extraction pipelines from mining reports and documents using OCR, layout understanding, multimodal models, and LLM techniques, with traceable, validated outputs. Create and evaluate machine learning solutions for predictive analytics, anomaly detection, and risk assessment, and contribute to graph-based knowledge and GraphRAG retrieval. Integrate solutions using Microsoft Azure AI services and collaborate with multidisciplinary teams on global mining projects.
Location: Noida, Mumbai
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Design, develop, and implement AI-enabled automation solutions for mining engineering and operational workflows.
  • •Develop automated pipelines to extract information from mining reports and documents using OCR, layout understanding, multimodal models, and LLM-based techniques.
  • •Develop, validate, and support deployment of machine learning solutions for predictive analytics, anomaly detection, classification, risk assessment, optimization, and asset insights.
  • •Support knowledge extraction and graph-based intelligence, including knowledge models, knowledge graphs, and GraphRAG-style retrieval workflows with provenance and auditability.
  • •Integrate AI workflows with engineering platforms and enterprise data environments using Azure AI services, including pipelines, APIs/connectors, deployment, monitoring, testing, and continuous improvement.

Key Requirements

  • •Bachelor’s or Master’s degree in Mining Engineering, Computer Science, Data Science, Artificial Intelligence, Software Engineering, Geotechnical Engineering, or a related discipline.
  • •Experience developing AI, machine learning, automation, data analytics, or document intelligence solutions in mining or asset-intensive environments.
  • •Proficiency in Python and relevant AI/data science/ML libraries and frameworks.
  • •Hands-on experience with large language models, prompt engineering, retrieval-augmented generation, or generative AI application development.
  • •Knowledge of data engineering (ETL/ELT pipelines, APIs, structured/unstructured processing, system integration) plus document processing (OCR, computer vision, layout/multimodal techniques).
Experience:MiningEngineeringInfrastructureIndustrialAsset-intensive environments
Education:Bachelor's in Mining Engineering, Computer Science, Data Science, Artificial Intelligence, Software Engineering, Geotechnical Engineering (or related discipline)
Skills:CollaborationCommunicationProblem-solving
Tech Stack:PythonGenerative AIMachine learningComputer visionOCRLayout understandingMultimodal modelsLLMPrompt engineeringRetrieval-augmented generationRAGGraphRAGRDFOWLSPARQLETLELTAPIsAzure AI servicesAzure OpenAI

Company Brief

WSP
Global professional services firm providing engineering, consulting, and technical services across infrastructure, environment, buildings, transportation, and energy sectors for public- and private-sector clients worldwide.
Industry: Professional Services
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Montreal, Canada
Founded: 1959
WebsiteLinkedIn