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Ai Alignment Jobs in Wisconsin (NOW HIRING)

WI · On-site

$130 - $160/hr

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 ...

New

WI · On-site

$134.30 - $236.10/hr

Executive Discovery and Strategic Alignment* Partner directly with executive stakeholders, business leaders, and enterprise architects to identify transformational opportunities using Genesys AI and ...

As the AI Program Manager, you will build and run a program of AI initiatives that create ... Run stage-gated delivery (scope → pilot → scale) aligned to HellermannTyton COE project ...

WI · On-site

$120 - $160/hr

Translate business needs into well‐architected AWS AI solutions, aligned with security, compliance, and cost‐optimization best practices.* Advise clients on AI adoption strategies, cloud ...

New

AI Solutions Architect

Milwaukee, WI · On-site

$62 - $81.50/hr

Responsibilities : • Design and deliver scalable AI-powered architectures that solve real customer problems and align with business strategy. • Serve as a trusted advisor to internal and external ...

WI · On-site

$130 - $190/hr

We are an AI-forward company committed to being a technology leader in our industry. NISC has been ... Mission Alignment: Ensure solutions are practical, intuitive, and aligned with the operational ...

New

Develop and align enterprise AI architecture on OCI, with a focus on generative AI capabilities and Oracle applications * Architect and deliver integrated AI solutions, including agentic workflows ...

Manager, AI Engineering

Milwaukee, WI · On-site

$140 - $190/hr

Ensure AI solutions align with enterprise architecture, Azure AI platform standards, cybersecurity requirements, responsible AI expectations, and ISC data governance requirements. * Team Leadership ...

New

Showing results 41-60

Ai Alignment information

What is AI alignment?

AI alignment refers to the process of ensuring that artificial intelligence systems act in ways that are aligned with human values, intentions, and ethical standards. This field focuses on designing AI models that not only achieve their objectives but also do so safely and beneficially for humanity. As AI systems become more advanced, alignment becomes increasingly important to prevent unintended consequences or harmful behaviors. Researchers in AI alignment work on technical solutions, such as value learning and interpretability, as well as broader ethical and policy considerations.

What is the difference between Ai Alignment vs Data Scientist?

AspectAi AlignmentData Scientist
Required CredentialsAdvanced degrees in AI, Machine Learning, or related fieldsDegree in Data Science, Statistics, Computer Science, or related fields
Work EnvironmentResearch labs, AI development companies, tech firmsTech companies, finance, healthcare, consulting firms
Industry UsageFocuses on ensuring AI systems behave as intendedAnalyzes data to extract insights and build predictive models

While both roles involve advanced technical skills, Ai Alignment specialists focus on aligning AI systems with human values and safety, whereas Data Scientists analyze data to inform business decisions. The roles often overlap in AI research environments but serve different primary objectives.

What are some common challenges faced by professionals working in AI alignment roles?

Professionals in AI alignment roles often encounter the challenge of translating complex ethical principles and human values into machine-understandable objectives. Balancing technical constraints with theoretical considerations requires close collaboration with cross-functional teams, including ethicists, engineers, and product managers. Additionally, the rapidly evolving landscape of artificial intelligence demands continuous learning to stay current with new alignment techniques and research findings. Navigating these challenges can be intellectually stimulating and offers significant opportunities for interdisciplinary growth.

What are the key skills and qualifications needed to thrive as an AI alignment specialist, and why are they important?

To thrive as an AI Alignment Specialist, you need a strong background in computer science, mathematics, and machine learning, often evidenced by an advanced degree in a related field. Familiarity with technical tools such as Python, TensorFlow, PyTorch, and formal verification systems is typically required, along with understanding of AI safety principles. Analytical thinking, ethical reasoning, and effective communication are crucial soft skills for success in this role. These skills ensure that AI systems are developed safely, ethically, and in alignment with human values, which is essential for mitigating risks associated with advanced AI.
What cities in Wisconsin are hiring for Ai Alignment jobs? Cities in Wisconsin with the most Ai Alignment job openings:
Infographic showing various Ai Alignment job openings in Wisconsin as of August 2026, with employment types broken down into 67% Full Time, and 33% Temporary. Highlights an 100% In-person job distribution.

$130 - $160/hr

Other

Posted 2 days ago

New


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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