Job Url: https://www.linkedin.com/jobs/search/?currentJobId=4341775393&distance=25&f_AL=true&f_TPR=r6000&f_WT=2&geoId=103644278&keywords=software%20engineer&origin=JOB_SEARCH_PAGE_JOB_FILTER&refresh=true&spellCorrectionEnabled=true Job Description: Azure Machine Learning Engineer United States · 27 minutes ago · 13 applicants Promoted by hirer · No response insights available yet $175K/yr - $205K/yr Remote Matches your job preferences, workplace type is Remote. Full-time Easy Apply Save Save Azure Machine Learning Engineer at Precise Resource, Inc Azure Machine Learning Engineer Precise Resource, Inc · United States (Remote) Easy Apply Save Save Azure Machine Learning Engineer at Precise Resource, Inc Show more options Your profile is missing required qualifications Show match details Help me update my profile BETA Is this information helpful? Get personalized tips to stand out to hirers Practice mock interviews personalized to every role and get custom feedback Try Premium for PKR0 Meet the hiring team Janis Mitchell 💫 3rd Founder | Entrepreneurship | Executive Search Job poster Message About the job Sr Web & Azure Machine Learning Engineer (Remote) NO H1B US CITIZEN or GREEN CARD ONLY PLEASE The search for a Senior Web & Azure Machine Learning Engineer (Remote) has begun! Precise Resource, Inc., the leading privately held Woman Business Enterprise specializing in Executive Search and HEAD HUNTING services for Fortune 500 clients across the United States, is on its way to finding you--a talented candidate with experience as an IT professional who can design websites that will draw traffic while meeting standards of SEO compliance. Our client has developed a new solution that enables eye doctors to remotely examine patients via video conference, controlling the phoropter at the site.This fantastic technology consolidates images/data to provide a more comprehensive view. Our Client is a fast-growing health-tech company modernizing eye care nationwide. We’re seeking a Senior Web & Azure ML Engineer who can own full-stack delivery and the ML lifecycle in Azure—from data to deployment—to power our Digital Tele-Optometry platform and AI features. What You’ll Do End-to-end ML in Azure: Train, evaluate, and deploy models using Azure Machine Learning Studio & the Azure ML SDK (Python). Package models as real-time/batch endpoints and integrate them into ASP.NET/Core services. MLOps at scale: Build CI/CD for ML with Azure DevOps (pipelines, artifacts, environments). Responsible AI & monitoring: Performance telemetry via AML monitoring/Azure Monitor. Production integration: Expose model inference securely to .NET/API backends (App Service/AKS); optimize latency, throughput, and cost. Web application delivery: Design, build, and scale cloud-native web apps (C#/ASP.NET, SQL, JavaScript) in Microsoft Azure—including real-time experiences (SignalR). Operational excellence: Establish incident playbooks, logging/alerting (App Insights). Collaboration: Work closely with web devs, designers, and cross-functional teams to deliver new functionality for a growing, AI-enabled platform. Tools & Stack You’ll Use Azure AML (workspaces, compute, registry, endpoints), App Service/AKS, /App Insights. Azure DevOps (Repos/Pipelines/Boards), Git, CI/CD for app & model, Infrastructure as Code. JavaScript/TypeScript (frameworks as applicable). Required Qualifications 7+ years building web applications (C#/ASP.NET, Web API, JavaScript/TypeScript). 5+ years on Microsoft Azure with production workloads (App Service, SQL, Storage, networking). Azure ML hands-on experience: training and deploying models with Azure ML Studio/SDK, model registry, endpoints, and monitoring. MLOps with Azure DevOps: pipelines for data + model CI/CD, gated releases, infrastructure-as-code (Bicep/Terraform or ARM), and secrets management. Data/Model fundamentals: feature engineering, evaluation, cross-validation, experiment tracking. SQL proficiency and production API integration of ML services into .NET apps running in Azure. Strong debugging/issue resolution skills across web apps and services. Nice to Have Government PIV familiarity and prior US government environment exposure. Experience with SignalR, pub-sub architectures, embedded video conferencing, and real-time UX. Experience building Whisper or speech-enabled applications/pipelines. Telerik / Kendo / DevExpress component libraries. Exposure to Azure Kubernetes Service