Azure MLOps Trainer Needed for Training Sessions

@alejandro2471

Thanks for your job posting. I am very familiar to Azure AI part for over 3 years so i am sure to handle your requirement fully. My previous project is similiar with your current thing. You can check my review on my profile page. I can start work immediately and look forward to having a detailed discussion through a chat. Thanks again. Regards

@Azursol

Hello,! I’m excited about the opportunity to help with your project. Based on your requirements, I believe my expertise in Python aligns perfectly with your needs. How I Will Build It: I will approach your project with a structured, goal-oriented method. Using my experience in Python, Azure, Machine Learning (ML), OCR, Enterprise Architecture, FastAPI, Azure OpenAI, MLOps, I’ll deliver a solution that not only meets your expectations but is also scalable, efficient, and cleanly coded. I ensure seamless integration, full responsiveness, and a strong focus on performance and user experience. Why Choose Me: - 10 years of experience delivering high-quality web and software projects - Deep understanding of Python and related technologies - Strong communication and collaboration skills - A proven track record — check out my freelancer portfolio. - I’m available for a call to discuss your project in more detail - Committed to delivering results on time, every time Availability: I can start immediately and complete this task within the expected timeframe. Looking forward to working with you! Best regards, Ali Zahid United Arab Emirates

@steveng96

Hello, and thank you for sharing this opportunity. I will share my wonderful previous project when we start a chat, so you can see my hands-on experience with production-grade Azure LLM systems. I have extensive experience delivering enterprise LLM pipelines on Azure, including OpenAI API integrations, full RAG workflows with vector/hybrid search, document ingestion, and secure deployments via AKS, Functions, and Container Apps. I’ve guided teams through live coding, architecture reviews, and production-level observability, ensuring clean architecture, error handling, and cost-efficient performance. For your training, I’ll create a structured roadmap, conduct hands-on live sessions with Python/FastAPI, and provide detailed code reviews, demonstrating real-world RAG + agentic workflows in production. My goal is to equip your team with practical skills, reliable patterns, and enterprise-ready implementations. I’m excited to help you achieve these outcomes smoothly and confidently.

@reactnodepython

Hello, I'm an Azure developer with over 10 years of experience in building enterprise-grade AI systems. We'll discuss the details in a chat. I understand you need a senior Azure AI engineer for hands-on training in LLM systems. My experience includes building production-ready applications with Azure OpenAI API, implementing full Retrieval-Augmented Generation (RAG) pipelines, and managing secure deployments using Azure Functions. I focus on clean architecture and performance considerations, which will be essential for your training sessions. For your training, I can offer the following options: Option A: A structured training roadmap that includes live coding sessions and architecture walkthroughs tailored to your team’s needs. Option B: A comprehensive capstone project where participants will deploy an enterprise RAG with an agent workflow on Azure, ensuring they gain practical skills from day one. Which option works best for you? Best, Yurii

@cindyviorinar

Hello, I’ve read your requirements carefully and I’m confident I can deliver focused, production-ready Azure MLOps training that skips theory and targets the operational issues you listed. I’ve shipped multiple enterprise LLM systems on Azure OpenAI and Azure AI Search, built reliable document ingestion pipelines (Blob → OCR → chunking → embeddings), and deployed RAG and agentic workflows with secure, managed identities and private endpoints. My hands-on sessions emphasize clean architecture, resilient production patterns (retries, structured validation, observability with App Insights), cost-aware performance tuning, and secure deployment via Container Apps/AKS and Azure Functions. I’ll provide a structured roadmap, live coding workshops, architecture walkthroughs, code reviews, and a capstone enterprise RAG+agent deployment you can run in your tenancy. If that fits, the next step is to align on trainees’ current infra, sample document types, and the level of access you can provide for live demos. Do you have an existing Azure subscription and sample documents (sizes/formats) we can use for the live ingestion and RAG capstone, and what is the expected trainee skill level with Azure services? Sincerely, Cindy Viorina

@mahamnoornaz06

Hello sir, I can deliver structured, hands-on Azure MLOps training focused strictly on production-grade LLM systems, not theory. With 5+ years building and deploying Azure OpenAI solutions, I’ve implemented full RAG pipelines using Azure AI Search (vector + hybrid), document ingestion flows (Blob, OCR, chunking, embeddings), agentic tool-calling workflows, and secure deployments via Functions, Container Apps, and AKS with Managed Identity and RBAC. My sessions emphasize clean architecture, observability, retries, validation, cost control, and DevOps pipelines. I’ll provide a roadmap, live coding, reviews, and a deployed enterprise capstone. Do you prefer FastAPI? Existing Azure subscription structure? If I am lucky enough to capture your attention, please don't hesitate to contact me. We can engage in a 10-15 minute discussion via messages to delve deeper into the project requirements and cover all aspects.

@danielboggs

Hello, I’ve read your requirements and can deliver senior, hands-on Azure MLOps training focused on production-grade LLM systems rather than theory or chatbots. I’ve shipped multiple Azure OpenAI + RAG systems into production and will guide your team through secure, observable implementations: production-ready Azure OpenAI integrations, end-to-end RAG with Azure AI Search, document ingestion (Blob → OCR → chunking → embeddings), function/tool-calling, and secure deployments (Functions/Container Apps/AKS) with RBAC and private endpoints. I’ll provide a structured roadmap, live coding, architecture walkthroughs, code reviews, and a capstone enterprise RAG + agent deployment. Training emphasizes clean architecture, error handling, observability, retries, performance tuning, and cost controls. I propose an initial 2-week engagement to deliver roadmap plus 3 live sessions and wrap-up capstone support. Which production environment and subscription constraints (VNETs, private endpoints, allowed regions, and tenant/managed identity policies) should I design the capstone around? Best regards, Daniel

@sumitwebrainbows

As a seasoned Azure AI engineer with an emphasis on Azure MLOps, I am confident in my ability to deliver the structured, practical training sessions you require. With years of experience building and successfully deploying real-world Azure LLM systems into production, I'm well-versed in everything from integrating Azure OpenAI API to secure Azure deployments using Managed Identity and RBAC. To illuminate my competence further, I'd like to mention my familiarity with key tools that are relevant to your project, including Azure AI Search (with vector search compatibility), Azure Document Intelligence or equivalent OCR software, as well as Python backend development using FastAPI - a robust framework for modern web apps. As we've worked through similar domains previously, I understand that your project needs go beyond generic prompt engineering and theory-based lectures. I'm here precisely to provide practical-based training, leveraging on the vast array of skills at my disposal. By choosing me for this project, you can expect not just live coding sessions and architecture walkthroughs but detailed implementation code reviews and a valuable enterprise RAG capstone to culminate the training.

@jonhw5

Hello, thanks for posting this project. Your requirements for advanced, production-focused Azure MLOps training closely match my experience delivering end-to-end LLM and RAG solutions in enterprise Azure environments. I have direct expertise in designing and deploying secure, production-grade workflows using Azure OpenAI, AI Search, robust ingestion (OCR/chunking/embeddings), and observability patterns across AKS, Functions, and Container Apps. My approach is highly hands-on, with clear, structured training roadmaps, live coding, and in-depth architecture reviews emphasizing security, performance, and cost control. I have successfully led similar training initiatives for enterprise teams, ensuring practical skills transfer and readiness for real-world deployment constraints. Could you share more about the primary audience for the sessions (roles/experience), so I can tailor the roadmap for maximum impact? Looking forward to discussing how I can support your team's upskilling goals.

@dev7fares

Hello, I am a freelance developer specializing in delivering tailored technology solutions across various projects and industries. I quickly adapt to different technologies and project requirements to ensure efficient and scalable results. I focus on providing clean, well-structured, and high-performance solutions that meet business objectives. I respect deadlines and maintain clear, professional communication throughout the collaboration. I am available to discuss your project and start immediately.

@Texxi

✨Hello, Client!✨, I am a new freelancer who has completed contract with the company and is currently working as a freelancer. I can deliver hands-on Azure MLOps training focused on real production systems, covering Azure OpenAI, RAG pipelines with Azure AI Search, and secure enterprise deployments. I have practical experience building LLM systems with FastAPI, document ingestion pipelines, OCR workflows, and implementing tool-calling agents with strong validation and retry logic. I look forward to working with you.

@slavkom1

Hi there. I see you need senior-level Azure MLOps training focused on real production work, not theory or demos. I’ve built and shipped Azure OpenAI and RAG systems for enterprise clients, so I can walk through the exact patterns you’re looking for. I’d keep the sessions practical and code‑driven: - Build Azure OpenAI integrations with retries and logging - Set up a full RAG pipeline with Azure AI Search - Implement ingestion from Blob through OCR, chunking, and embeddings - Add tool-calling patterns and deploy through Functions or Container Apps - Review architecture choices and harden everything with RBAC and managed identities I can start right away and run the sessions in short, focused blocks. Which part of the RAG pipeline do you want to deep‑dive first: ingestion, indexing, or retrieval logic? Cheers, Slavko

@juanestebana17

Hello, Hi, I have shipped multiple Azure LLM systems into production for enterprise clients, and I specialize in building secure, observable, cost-conscious pipelines. I will deliver hands-on, code-first training focused on production-ready Azure OpenAI integrations, RAG with Azure AI Search, secure deployments, and observability patterns. I will provide a structured roadmap, live coding, architecture walkthroughs, code reviews, and a capstone enterprise RAG + agent deployment matching your constraints. I will emphasize clean architecture, retries, structured validation, performance tuning, and RBAC/private endpoints so your team can reproduce and operate these systems safely in production. Which existing Azure services, repositories, or sample datasets do you want me to use during live coding (e.g., an existing Storage account, private VNet, or specific document corpus)? Best regards, Juan Aponte

@simar2176

Hello, Greetings of the day. This aligns directly with my enterprise AI architecture experience. I have 9+ years of engineering background, including enterprise exposure at TCS and Infosys, and have implemented production-grade Azure LLM systems with structured RAG pipelines and secure cloud deployment patterns. I can deliver hands-on, architecture-first training focused strictly on production implementation — no theory-heavy sessions, no UI fluff. What I will cover: Azure OpenAI in production • Managed identity authentication • Structured prompt orchestration • Function/tool calling patterns • Token control and cost governance Enterprise RAG on Azure • Blob storage ingestion pipeline • OCR via Azure Document Intelligence • Chunking + embedding strategy • Azure AI Search (vector + hybrid search) • Metadata filtering and ranking tuning Agentic Workflows • Tool-calling orchestration layer • Validation + structured output enforcement • Retry logic and fallback handling Deployment & MLOps • FastAPI backend architecture • Azure Functions / Container Apps / AKS deployment patterns Deliverables include a structured roadmap, live coding sessions, architecture walkthroughs, code reviews, and a capstone enterprise RAG + agent deployment on Azure. This will be practical, production-grade, and enterprise-focused from day one.

@Nelson018

Skillful SOFTWARE SPECIALIST HERE!! Hi Nice to meet you I just read your job description and I can do your project perfectly. I have over 15 years of experience in development. Contact me Nelson

@venplura

Hi there! Are you planning to cover multi-tenant security scenarios within the RBAC and private endpoints in the training sessions? Regardless, this is definitely something that I feel confident delivering on, given my past experience. I would love to discuss your project further! Looking forward hearing from you. Kind Regards, Corné

@ayseorkan

I am an AI-focused software developer with a solid foundation in software engineering and a strong interest in artificial intelligence and machine learning. With two years of hands-on experience, I have developed strong skills in ERP solutions, software testing, system development, and integration across various industries. I am highly motivated, detail-oriented, and committed to delivering clean, efficient, and scalable solutions. If you are looking for a developer who combines technical fundamentals with a strong drive to grow in AI, I would be excited to contribute to your project.

@jack0192

As an experienced software engineer with a strong emphasis on Python development, I'm well-suited to meet the demanding requirements of your Azure AI training project. Throughout my career, I have continuously sought to push the boundaries of my understanding in order to develop complex, real-world systems such as the ones you are seeking to build and teach about. This has entailed mastering various tools and technologies including Azure OpenAI, Azure AI Search with vector search, and Azure Document Intelligence, among others, all of which align closely with your needs. Moreover, I emphasize production-readiness in my work; clean architecture, observability, error handling and performance considerations are all crucial elements of systems that truly 'work'. I’ve gained invaluable insights from shipping several Azure LLM systems into production - through learning from failures and successes alike - which greatly enhances my capacity to provide depth and relevant case studies throughout your training program.

@yeswanthmedida19

Hello, This aligns well with my experience building production-grade Azure LLM systems with secure deployment and clean architecture patterns. I understand this is not a theory course. The focus is enterprise-ready MLOps, observability, reliability, and secure Azure-native design. Proposed Training Architecture Flow • Azure OpenAI integration with structured validation layer • Full RAG pipeline: Blob → OCR (Document Intelligence) → chunking → embeddings → Azure AI Search (vector + hybrid) • Agentic workflows using function/tool-calling patterns • FastAPI backend with retry logic, validation, and logging • Secure deployment via Azure Functions or Container Apps • Managed Identity, RBAC, private endpoints • Observability via Application Insights • CI/CD using Azure DevOps or GitHub Actions Each session will include live coding, architectural reasoning, and production trade-off discussions. Final capstone: enterprise RAG + agent workflow deployed securely on Azure. Estimated hours: 30–35 Rate: $8/hr Timeline: 3–4 weeks Happy to share structured roadmap outline before kickoff.