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The Lead Machine Learning Engineer will design and implement scalable machine learning solutions, lead teams, and analyze large datasets using cloud technologies.

Lead Machine Learning Engineer is responsible for designing and implementing data-driven solutions, optimizing and deploying machine learning systems, and mentoring junior staff while working collaboratively across teams.

The Lead Machine Learning Engineer at CapTech designs and implements scalable machine learning systems, collaborates with teams, and provides technical leadership while optimizing enterprise data-driven solutions.

The Machine Learning Engineer designs and implements scalable solutions for clients, analyzing datasets, productionizing ML systems, and leading teams.

The Machine Learning Engineer designs and implements data-driven solutions, develops scalable ML systems, analyzes datasets, and leads client collaborations.

Develop and maintain enterprise full-stack applications, integrations, APIs, microservices, distributed systems, cloud and serverless solutions, and web front ends using the .NET ecosystem. Collaborate with clients and technical teams, apply object-oriented design patterns, communicate technical solutions, mentor developers, and deliver scalable, optimized, well-documented software in a project-based consulting environment. The role requires working onsite five days per week.

Leads complex technology projects and consulting engagements across cross-functional teams. Develops project plans and roadmaps, manages milestones, risks, deliverables, and critical issues, facilitates stakeholder decisions, and applies Agile, Waterfall, or hybrid methodologies. The role also performs hands-on analysis, design, process engineering, and change management while supporting account management and developing project management capabilities.

Leads complex technology consulting projects and cross-functional delivery teams. Responsibilities include managing Agile, Waterfall, or hybrid methodologies; developing project plans and roadmaps; tracking milestones, risks, and deliverables; facilitating stakeholder decisions; resolving critical issues; and supporting analysis, design, process engineering, and change management. The role requires experience leading Microsoft Dynamics 365 and Power Platform implementations, integrating enterprise systems, and managing large CRM and ERP projects.

Build and maintain deployment, monitoring, alerting, infrastructure automation, and continuous integration systems across physical, private-cloud, and public-cloud environments. Define and improve SDLC, configuration, release, and deployment strategies; troubleshoot distributed systems; collaborate across development and operations teams; and contribute to software development as needed.

Leads complex technology consulting engagements and cross-functional delivery teams. Develops project plans and roadmaps, manages milestones, risks, issues, and stakeholder decisions, and applies Agile, Waterfall, or hybrid methodologies. Performs hands-on analysis, design, process engineering, and change management as needed. The role emphasizes Microsoft Dynamics 365 and Power Platform implementations, CRM and ERP projects, enterprise integrations, client relationship management, and mentoring project management professionals.