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Chatbot Training Jobs in Michigan (NOW HIRING)

$111K - $146K/yr

This is not a pure research or model-training role. We are looking for someone who can build real ... Build and support chatbot, RAG, conversational AI, and model-connected application capabilities.

New

This is not a pure research or model-training role. We are looking for a hands-on technical leader ... Lead or support chatbot, RAG, conversational AI, agentic AI, and AI assistant integration ...

New

We will give you the training and opportunities to unleash your ambition. Summary: * We are seeking ... This role is essential to ensuring our chatbot delivers accurate, accessible, and high-quality ...

This is not a pure research or model-training role. We are looking for someone who is curious ... tools, chatbot-style workflows, and internal AI capabilities. - Assist with MCP development ...

New

This is not a pure research or model-training role. We are looking for someone who is curious ... tools, chatbot-style workflows, and internal AI capabilities. - Assist with MCP development ...

New

This is not a pure research or model-training role. We are looking for someone who is curious ... tools, chatbot-style workflows, and internal AI capabilities. - Assist with MCP development ...

New

$93K - $122K/yr

This is not a pure research or model-training role. We are looking for a technical leader who can ... What would be a plus? -Experience leading enterprise AI, GenAI, chatbot, RAG, or AI assistant ...

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... training. Compensation Range: $95,300.00 - $119,100.00 Compensation may vary based on applicant ... AI Agent & Chatbot Projects * AI Workflow Projects * Predictive Modeling Projects * Educate Finance ...

Chatbot Training information

What are the key skills and qualifications needed to thrive as a Chatbot Trainer, and why are they important?

To thrive as a Chatbot Trainer, you need a strong understanding of natural language processing (NLP), data annotation, and linguistic analysis, typically supported by a background in linguistics, computer science, or a related field. Familiarity with annotation tools, training platforms like Dialogflow or Rasa, and knowledge of data labeling standards and processes is essential. Attention to detail, critical thinking, and clear communication are important soft skills for effective data labeling and iterative improvement. These skills ensure that chatbots are trained accurately and efficiently, leading to better conversational AI performance and user satisfaction.

What is chatbot training?

Chatbot training is the process of teaching a chatbot how to understand and respond to user inputs effectively. This involves feeding the chatbot with example conversations, questions, and answers so it can learn to interpret language, context, and intent. Training can be done using rule-based approaches, machine learning, or a combination of both. The goal is to improve the chatbot’s accuracy and ability to provide helpful, human-like responses.

What is the difference between Chatbot Training vs Chatbot Developer?

AspectChatbot TrainingChatbot Developer
Required SkillsNatural Language Processing, data annotation, machine learning basicsProgramming, software development, API integration
Work EnvironmentData labeling, model refinement, content creationCoding, system design, deployment
CertificationsAI/ML certifications, NLP coursesSoftware development certifications, coding bootcamps
Industry UsageTraining AI models for chatbots, improving understandingBuilding and maintaining chatbot platforms and applications

Chatbot Training focuses on preparing AI models through data annotation and refining language understanding, while Chatbot Developers build and implement the chatbot systems using programming skills. Both roles are essential in creating effective chatbots but differ in technical complexity and daily tasks.

What are some common challenges faced by professionals working in chatbot training, and how can they address them?

Professionals in chatbot training often encounter challenges such as ensuring the chatbot understands various user intents, handling ambiguous language, and continuously improving the bot's responses based on user feedback. Collaborating closely with data scientists, developers, and UX designers is essential to iteratively refine training data and conversational flows. Staying updated with advancements in natural language processing (NLP) can also help address limitations and maintain a high-quality user experience. Regular review of chat logs and user interactions is key to identifying areas for improvement.
What cities in Michigan are hiring for Chatbot Training jobs? Cities in Michigan with the most Chatbot Training job openings:
Infographic showing various Chatbot Training job openings in Michigan as of July 2026, with employment types broken down into 2% Locum Tenens, 48% As Needed, 18% Full Time, 4% Part Time, 26% Nights, and 2% Summer. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution.
Sr. AI Engineer

$111K - $146K/yr

Full-time

Posted 5 days ago

New


Corning rating

8.2

Company rating: 8.2 out of 10

Based on 127 frontline employees who took The Breakroom Quiz

84th of 527 rated manufacturers


Job description

Are you passionate about building practical AI solutions that can scale in an enterprise environment?

At Corning, we are looking for a Sr. AI Engineer to help design, build, implement, and support AI-enabled applications, tools, agents, and integrations that support business needs across Corning Optical Communications.

This role is part of our Digital & IT organization and is focused on applying AI through hands-on software engineering, application development, Python, APIs, LLM-enabled solutions, and enterprise integrations. This is not a pure research or model-training role. We are looking for someone who can build real, supportable AI solutions that can be used by business and technical users.

What will you do?

Design, build, test, implement, and support AI-enabled applications, tools, agents, automations, and integrations.

Develop Python-based solutions and work with APIs, JSON payloads, model integrations, and LLM-enabled workflows.

Partner with business and technical stakeholders to translate requirements into practical AI solutions.

Build and support chatbot, RAG, conversational AI, and model-connected application capabilities.

Contribute to application development efforts that make AI agents and tools easier for users to access and use.

Support solution quality through debugging, testing, documentation, troubleshooting, and post-deployment stabilization.

Help create reusable patterns, improve engineering practices, and mentor less experienced engineers when needed.

What do you need to have?

Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Data Science, or a related technical discipline.

4+ years of relevant experience in software engineering, AI engineering, application development, automation, integration development, or related technical solution delivery.

Strong hands-on experience with Python.

Experience working with APIs, JSON payloads, integrations, and application/service development.

Professional experience building or supporting AI-enabled applications, LLM-based solutions, chatbots, RAG solutions, agents, automations, or model-connected workflows.

Experience participating in technical projects within a company or business environment, not only personal experimentation with AI tools.

Strong understanding of software development fundamentals such as debugging, testing, version control, documentation, and maintainable coding practices.

Ability to communicate effectively with technical teams and business stakeholders.

Advanced English communication skills.

What would be a plus?

Experience with enterprise AI assistants, chatbot platforms, internal AI tools, or AI-enabled productivity platforms.

Experience with RAG, prompt engineering, agentic AI, orchestration patterns, or MCP development.

Experience with Databricks or Databricks Genie Spaces.

Experience with model-serving endpoints or managed AI services.

Experience with tools such as ChatGPT, Claude, Copilot, Codex, or similar AI-assisted development tools.

Cloud experience with Azure, AWS, or GCP.

Experience mentoring junior engineers or helping define reusable development patterns.

Experience in manufacturing technology, enterprise software, automation, workflow platforms, or internal productivity platforms.

What should we offer?

Opportunity to be part of a growing AI engineering team focused on practical enterprise AI solutions.

Exposure to modern AI technologies, LLM applications, agents, automation, chatbot/RAG solutions, and enterprise integrations.

A hybrid role based in Obispado, Monterrey, with most work expected to be remote and office presence as needed.

Opportunity to influence how AI is adopted and scaled across Corning Optical Communications.

Career growth in AI engineering, technical leadership, enterprise application development, and AI platform enablement.

More about us

Corning is one of the world’s leading innovators in glass, ceramic, and materials science. From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries of what’s possible.At Corning, there are endless possibilities for making an impact. You can help connect the unconnected, drive the future of automobiles, transform at-home entertainment, and ensure the delivery of lifesaving medicines. And so much more.Come break through with us.Corning is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.


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