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Scale Ai Jobs (Flexible Options) in Wisconsin

WI · On-site

$130 - $160/hr

Position Summary The Sr AI Engineer serves as a technical leader responsible for enterprise-scale AI architecture, solution governance, and advanced AI engineering practices. This role drives ...

WI · On-site

You will mentor engineering leaders, drive governance, and scale AI-driven consumer experiences, while ensuring quality, safety, and data #J-18808-Ljbffr

WI · On-site

$150 - $210/hr

Tiger Analytics looking for an experienced Enterprise AI Architect to lead the design and implementation of enterprise-scale AI platforms and intelligent applications. In this role, you will define ...

WI · On-site

$100 - $130/hr

About Bitdeer Bitdeer is a world-leading technology company for Bitcoin mining and AI cloud ... Deploy and manage large-scale GPU clusters using orchestration platforms such as Kubernetes or ...

Senior AI Engineer

Middleton, WI · On-site

$107K - $147K/yr

The Sr AI Engineer is a hands-on technical leader who ships enterprise-scale AI into production and owns the architecture, governance, and engineering practices that turn ambitious ideas into working ...

Senior AI Engineer

Middleton, WI · On-site

$107K - $147K/yr

The Sr AI Engineer is a hands-on technical leader who ships enterprise-scale AI into production and owns the architecture, governance, and engineering practices that turn ambitious ideas into working ...

Senior AI Engineer

Middleton, WI · On-site

$107K - $147K/yr

The Sr AI Engineer is a hands-on technical leader who ships enterprise-scale AI into production and owns the architecture, governance, and engineering practices that turn ambitious ideas into working ...

Senior AI Engineer

Milwaukee, WI · On-site

$120K - $159K/yr

Architect and scale AI-enhanced systems, ensuring security, scalability, and high performance. * Integrate AI-driven capabilities such as chatbot assistants, image-based diagnostics, and automated ...

Senior AI Engineer

Milwaukee, WI · On-site

$120K - $159K/yr

Architect and scale AI-enhanced systems, ensuring security, scalability, and high performance. * Integrate AI-driven capabilities such as chatbot assistants, image-based diagnostics, and automated ...

WI · On-site

$184 - $287.50/hr

Experience with AI factory or large-scale AI infrastructure build, deployment, or operations.* Background in HPC systems engineering, SRE, or systems analysis for GPU-accelerated environments.

This role involves architecting and scaling AI-powered solutions, mentoring senior engineers, and collaborating with leadership to define and execute AI-driven strategies. Your leadership will extend ...

Build and scale AI and automation capabilities, such as recommendation engines, intelligent routing, chatbots, document processing, claims processing, and marketing personalization, to enhance member ...

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$130 - $160/hr

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Job description

Position Summary

The Sr AI Engineer serves as a technical leader responsible for enterprise-scale AI architecture, solution governance, and advanced AI engineering practices. This role drives strategic AI adoption and mentors engineering teams across the organization. This role will partner closely with Information Technology, business stakeholders, operations, customer service, product development, and analytics teams to deliver scalable AI capabilities that improve efficiency, enhance customer experiences, and enable data-driven decision making.

The ideal candidate combines strong software engineering fundamentals with practical expertise in machine learning, generative AI, data engineering, automation, and cloud technologies. This individual must be comfortable operating in a fast-paced, transformation-oriented environment and capable of translating business problems into production-ready AI solutions.

Key Responsibilities
  • Design, build, deploy, and maintain enterprise AI and machine learning solutions.
  • Develop and operationalize generative AI applications leveraging large language models (LLMs), retrieval-augmented generation (RAG), copilots, and intelligent automation.
  • Partner with business leaders to identify high-value AI use cases aligned to strategic priorities.
  • Build scalable AI pipelines, APIs, and integrations with enterprise platforms and business applications.
  • Collaborate with data engineering teams to ensure high-quality, governed, and accessible data for AI initiatives.
  • Develop AI-enabled analytics and predictive models supporting manufacturing, supply chain, customer service, sales, and operations.
  • Implement AI governance, model monitoring, security, and responsible AI practices.
  • Optimize model performance, scalability, reliability, and operational efficiency.
  • Evaluate emerging AI technologies and recommend enterprise adoption strategies.
  • Support AI experimentation, rapid prototyping, and innovation initiatives across the organization.
  • Create technical documentation, operational procedures, and knowledge transfer materials.
  • Mentor technical teams and promote AI engineering best practices.
Requirements

Required

  • Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.
  • Advanced degree in Artificial Intelligence, Machine Learning, or Data Science preferred.
  • 8-10+ years overall technology experience
  • 5+ years focused in AI/ML engineering
  • Proven experience deploying enterprise-scale AI systems
  • Experience leading technical teams or major initiatives
  • Strong experience with AI architecture and distributed systems
  • Experience operationalizing generative AI at scale
  • Executive communication capability

Preferred

  • Experience with Microsoft Copilot, Azure OpenAI, or enterprise generative AI platforms.
  • Manufacturing, supply chain, consumer products, or retail industry experience.
  • Experience with MLOps, vector databases, orchestration frameworks, and AI observability platforms.
  • Familiarity with data visualization and analytics platforms such as Power BI or Tableau.
  • Experience leading enterprise AI transformation initiatives.
  • AI governance frameworks
  • FinOps for AI workloads
  • Multi-cloud AI strategy
  • Experience building internal AI platforms or copilots
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