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Natural Language Processing Jobs in Wisconsin (NOW HIRING)

Direct Supply

Staff Software Engineer

Milwaukee, WI · On-site

... natural language processing, computer vision, and generative models. Preferred : • Experience leading AI-first engineering transformations across teams. • Contributions to open-source AI projects ...

Direct Supply

Senior Software Engineer

Milwaukee, WI · On-site

$120K - $158K/yr

... natural language processing, computer vision, and generative models. Preferred : • Contributions to open-source AI projects or AI research. • Experience with agentic AI frameworks (LangChain ...

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$14

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$48

How much do natural language processing jobs pay per hour?

As of Jul 4, 2026, the average hourly pay for natural language processing in Wisconsin is $25.71, according to ZipRecruiter salary data. Most workers in this role earn between $17.69 and $29.86 per hour, depending on experience, location, and employer.

Which 3 jobs will survive AI?

Natural Language Processing (NLP) specialists, data scientists, and AI ethics professionals are likely to continue thriving as AI advances, due to their expertise in developing, managing, and overseeing AI systems. These roles require specialized skills in machine learning, programming, and critical thinking that are less easily automated. Continuous learning and certification in AI tools and algorithms can help ensure job security in this evolving field.

What are the key skills and qualifications needed to thrive in the Natural Language Processing position, and why are they important?

To thrive in Natural Language Processing, you need strong expertise in linguistics, statistics, and machine learning, typically supported by a degree in computer science, computational linguistics, or a related field. Familiarity with tools and frameworks such as Python, TensorFlow, PyTorch, spaCy, and NLP libraries, as well as certifications in data science or NLP, are valuable assets. Analytical thinking, problem-solving skills, and the ability to collaborate across multidisciplinary teams are highly desirable. These competencies are essential for developing powerful language models, extracting meaningful insights from data, and delivering effective real-world solutions in language technology.

What are some typical challenges faced by professionals in Natural Language Processing roles?

Professionals in Natural Language Processing (NLP) often encounter challenges such as understanding ambiguities in human language, managing large and unstructured datasets, and keeping up with rapid advances in NLP methodologies. They may also need to fine-tune models for domain-specific contexts and ensure solutions meet ethical and privacy guidelines. Collaboration with data scientists, linguists, engineers, and product teams is common, requiring strong communication skills. Successfully tackling these challenges is a critical part of developing robust NLP applications that add meaningful value to users and businesses.

What is a Natural Language Processing job?

A Natural Language Processing (NLP) job involves developing and improving algorithms that enable computers to understand, interpret, and generate human language. Professionals in this field work on tasks like speech recognition, text analysis, machine translation, and chatbot development. They often use machine learning, deep learning, and linguistic principles to build and refine NLP models. NLP experts commonly work in industries such as healthcare, finance, and technology to enhance communication and automate language-related tasks.

Is Natural Language Processing a good career?

Natural Language Processing (NLP) is a growing field within artificial intelligence that involves developing algorithms to understand and generate human language. It offers opportunities in industries such as tech, healthcare, and finance, often requiring skills in machine learning, programming, and data analysis. Careers in NLP can be rewarding with high demand for expertise and competitive salaries.

What can I do with Natural Language Processing?

A Natural Language Processing (NLP) professional develops systems that enable computers to understand, interpret, and generate human language. This includes tasks like sentiment analysis, language translation, chatbots, and speech recognition, often using tools such as Python, NLP libraries, and machine learning models. NLP roles require strong programming skills and knowledge of linguistics or data science.

Does NLP pay well?

Natural Language Processing (NLP) specialists typically earn competitive salaries, especially with experience in machine learning, deep learning, and programming languages like Python. Salaries vary by industry, location, and level of expertise but generally reflect the high demand for skills in AI and data analysis.
What are the most commonly searched types of Natural Language Processing jobs in Wisconsin? The most popular types of Natural Language Processing jobs in Wisconsin are:
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Natural Language Processing jobs near you
Staff Software Engineer

Staff Software Engineer

Direct Supply

Milwaukee, WI • On-site

Full-time

Posted 23 hours ago

Job description

Job Summary:
Direct Supply is building the future of healthcare technology with industry-leading products, solutions and platforms to help improve the lives of millions of seniors and those who care for them. In the Staff Software Engineer position, you’ll play a critical role in shaping AI-first engineering practices, setting technical direction, and driving the adoption of cutting-edge AI capabilities across multiple teams.
Responsibilities:
• Define and execute the AI engineering strategy, embedding AI-first principles across teams and projects.
• Architect and scale AI-enhanced systems, integrating LLMs, agentic workflows, and composable architectures.
• Mentor engineers, sharing expertise in AI-first methodologies and best practices.
• Lead cross-functional AI initiatives, incorporating NLP, computer vision, and generative AI into products.
• Implement AI-powered developer tools to streamline development and boost efficiency.
• Drive experimentation and bridge the gap between AI research and production-ready applications.
• Partner with leadership to develop AI adoption roadmaps aligned with business objectives.
• Ensure security, scalability, and AI observability throughout the software lifecycle.
• Make key decisions on technical trade-offs, architecture, and AI tooling.
Qualifications:
Required:
• 8+ years of software engineering experience, including 3+ years leading AI-powered application development.
• Bachelor’s degree in Computer Science, Computer Engineering, or related field.
• Proven experience developing, deploying, and scaling AI-powered applications (provide examples of integrations using open models or APIs).
• Expertise in designing AI-first architectures, including microservices, event-driven systems, and real-time AI workflows.
• Hands-on experience with LLMs, agentic AI models, and autonomous AI-driven workflows.
• Strong skills in AI model deployment, cost optimization, and fine-tuning.
• Deep understanding of security, compliance, and ethical considerations in AI development.
• Ability to mentor and influence senior engineers in AI-first development methodologies, fostering a culture of innovation and technical excellence.
• Technical expertise in AI integration across natural language processing, computer vision, and generative models.
Preferred:
• Experience leading AI-first engineering transformations across teams.
• Contributions to open-source AI projects or AI thought leadership.
• Experience with agentic AI frameworks, composable AI solutions, and MLOps best practices.
• Industry engagement through conferences, research initiatives, or AI-first development communities.
• Cloud-native AI deployment experience (Docker, Kubernetes, cloud platforms).
Company:
The Direct Supply family of companies cares for every critical area of Senior Living, providing everything from equipment and eCommerce to Founded in 1985, the company is headquartered in Milwaukee, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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