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AI Engineer Artificial Intelligence, Machine Learning & Generative AI Emarat Maritime | Mumbai Salary: 914 LPA Experience: 37 Years | Permanent | Full-Time Build the Future of AI in Maritime Operations Emarat Maritime is looking for an innovative and hands-on AI Engineer to join our technology team and help drive the next generation of digital transformation across our vessel and shore operations. This is an exciting opportunity for an AI/ML professional who wants to work on real-world business problems involving Artificial Intelligence, Machine Learning, Generative AI, Large Language Models (LLMs), RAG, AI Copilots and intelligent automation. You will design, develop and deploy secure, scalable and production-ready AI solutions that improve operational efficiency, reduce manual effort and enable smarter, data-driven decision-making across the organisation. What You'll Work On You will work at the intersection of AI, software engineering, data and business operations, developing solutions that integrate with enterprise platforms and real-world operational data. From building predictive ML models and AI-powered applications to developing LLM-based copilots, chatbots and RAG systems, you'll have the opportunity to take AI solutions from concept to production. Key ResponsibilitiesArtificial Intelligence & Machine Learning Design, develop and deploy AI/ML models and AI-powered business applicationsBuild, train and productionise machine learning and deep learning modelsDevelop Generative AI solutions using Large Language Models (LLMs)Build AI chatbots, copilots and virtual assistantsDevelop predictive and data-driven solutions for real-world business use casesEvaluate emerging AI technologies and identify opportunities for business adoptionGenerative AI & LLMs Develop RAG (Retrieval-Augmented Generation) solutions for company knowledge bases and intelligent searchBuild AI copilots using Microsoft Copilot StudioDevelop prompt engineering frameworks and optimise LLM performanceFine-tune AI models where applicableBuild solutions for document summarisation, report generation and natural-language searchIntegrate AI models with enterprise applications and APIsEnterprise AI Integration Integrate AI solutions with ERP, SharePoint, Microsoft 365 and other enterprise platformsDevelop AI-enabled web applications, REST APIs and Python backend servicesIntegrate AI capabilities with existing business systemsSupport frontend development for AI-powered applicationsWork with Microsoft Power Platform to enable intelligent workflow automation and RPA solutionsAI Platform & MLOps Deploy AI/ML models using Azure AI, Azure Machine Learning, OpenAI or equivalent platformsManage AI environments and model lifecyclesImplement model versioning and deployment pipelinesMonitor AI services for performance, reliability and cost optimisationImplement model monitoring and drift detectionEnsure AI solutions are scalable, secure and production-readyData Engineering Collect, clean, transform and prepare structured and unstructured datasetsBuild ETL/ELT pipelines for AI applicationsDesign and maintain data lakes and AI datasetsEnsure data quality, integrity and governanceIntegrate data from ERP systems, IoT devices, vessel systems, APIs and cloud platformsMust-Have Skills 37 years of hands-on experience in AI/ML developmentStrong proficiency in PythonHands-on experience with Machine Learning / Deep LearningExperience with TensorFlow, PyTorch or equivalent ML frameworksExperience building and deploying production AI/ML modelsHands-on experience with Generative AI and LLMsExperience with RAG, chatbots, copilots or AI assistantsKnowledge of Azure AI / Azure Machine Learning / OpenAI or equivalent cloud AI platformsExperience integrating AI models with APIs and enterprise applicationsExperience working with structured and unstructured datasetsStrong understanding of data pipelines and AI application developmentGood to Have Experience with Microsoft Copilot StudioExperience with Microsoft Power Platform / Power AutomateExperience with ERP, SharePoint or Microsoft 365 integrationsKnowledge of MLOps and model lifecycle managementExperience with AI-enabled web applications and REST APIsExperience working with IoT, operational or enterprise datasetsExposure to maritime, shipping or IT servicesUnderstanding of AI governance, data privacy and cybersecurity standardsEducation Minimum Qualification: Bachelor's degree in Computer Science, Information Technology, Electronics, Engineering, STEM or a related discipline. Preferred: Master's degree in Artificial Intelligence, Machine Learning, Data Science or a related field. Security, Governance & Responsible AI The successful candidate will be expected to build AI solutions that meet enterprise security and governance standards, including: Compliance with ISO/IEC 27001Data privacy and security requirementsCompany AI and data governance policiesSecure integration with enterprise .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.