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Entry Level Chatbot Train Ai Jobs (NOW HIRING)

Simulmedia

Generative AI Analyst

New York, NY · On-site +1

$50K - $60K/yr

We seek an entry-level AI Analyst to join our team to research, prototype and implement AI ... Train and educate team members on effectively leveraging AI technologies Create and deliver ...

Simulmedia

Generative AI Analyst

New York, NY · On-site

$50K - $60K/yr

We seek an entry-level AI Analyst to join our team to research, prototype and implement AI ... Train and educate team members on effectively leveraging AI technologies • Create and deliver ...

Simulmedia

Generative AI Analyst

New York, NY · On-site +1

$50K - $60K/yr

We seek an entry-level AI Analyst to join our team to research, prototype and implement AI ... Train and educate team members on effectively leveraging AI technologies ● Create and deliver ...

Greenwood Project

AI Enablement Lead

Chicago, IL · On-site

... entry-level professionals won't reach for years. You'll be the person who makes that happen. What ... Train and coach every staff member to become a confident, capable AI user-meeting people where they ...

Greenwood Project

AI Enablement Lead

Chicago, IL

$95K - $115K/yr

... entry-level professionals won't reach for years. You'll be the person who makes that happen. What ... every person you train contributes to creating $45 million in economic mobility for ...

Adobe

Principal Product Manager, AEM Sites

San Jose, CA

$148K - $282K/yr

About the Role Every AI agent needs to ground its answers somewhere - the customer chatbot, the ... Partner with design, engineering, and product marketing to shape vision, GTM, and pricing; train ...

Mem0

Research Engineer - Agent Memory

San Francisco, CA · On-site

$175K - $250K/yr

... chatbot and something that actually knows you. We're already powering millions of AI interactions ... Train models: Memory extraction, updates, consolidation/forgetting, and conflict resolution ...

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Entry Level Chatbot Train Ai information

See salary details

$24K

$104.9K

$189K

How much do entry level chatbot train ai jobs pay per year?

As of Jul 23, 2026, the average yearly pay for entry level chatbot train ai in the United States is $104,863.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $120,000.00 per year, depending on experience, location, and employer.

What are some typical daily tasks for an Entry Level Chatbot Train AI position?

As an Entry Level Chatbot Train AI, your daily tasks usually involve reviewing and labeling chat conversations, identifying patterns in user queries, and providing feedback to improve the AI's language understanding. You may also help create or refine conversation scripts, test chatbot responses for accuracy, and document any issues you encounter. Collaboration with data scientists and engineers is common to ensure your insights help advance the chatbot's performance. This role is structured, detail-oriented, and offers the opportunity to learn about AI development from the ground up.

What are the key skills and qualifications needed to thrive as an Entry Level Chatbot AI Trainer, and why are they important?

To thrive as an Entry Level Chatbot AI Trainer, you typically need strong written communication skills, attention to detail, and a basic understanding of language processing, often supported by a bachelor's degree in a related field. Familiarity with annotation tools, content management systems, and sometimes basic programming or data labeling platforms is commonly required. Adaptability, problem-solving, and collaborative teamwork are valuable soft skills that help you excel in training AI models. These skills ensure that chatbot responses are accurate, contextually appropriate, and continuously improving for better user experiences.

What is the difference between Entry Level Chatbot Train Ai vs Data Annotator?

AspectEntry Level Chatbot Train AiData Annotator
Required CredentialsHigh school diploma or equivalent; some roles may prefer basic technical skillsHigh school diploma or equivalent; attention to detail essential
Work EnvironmentRemote or office-based; involves working with AI systems and softwarePrimarily remote or office-based; involves reviewing and labeling data
Industry UsageAI development, customer service automationData management, machine learning training
Common Search/ComparisonYesNo

Entry Level Chatbot Train Ai roles focus on training AI chatbots by providing conversational data, while Data Annotators label and categorize data for machine learning. Both roles require attention to detail and are essential in AI development, but they differ in specific tasks and focus areas.

What does an entry level chatbot AI trainer do?

An entry level chatbot AI trainer is responsible for teaching and improving artificial intelligence systems that power chatbots. Their daily tasks typically include reviewing chatbot conversations, labeling data, correcting errors, and providing feedback to help the AI understand language better. They work with teams of engineers and data scientists to ensure the chatbot can respond accurately and naturally to user questions. This role often requires attention to detail, good communication skills, and sometimes basic knowledge of programming or data annotation tools.
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Entry Level Chatbot Train Ai jobs near you
Infographic showing various Entry Level Chatbot Train Ai job openings in the United States as of July 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $104,863 per year, or $50.4 per hour.
Model Engineer - Member of Technical Staff

Model Engineer - Member of Technical Staff

Meter, Inc

San Francisco, CA • On-site

Full-time

Posted 3 days ago

Job description

Build the AI infrastructure layer of the physical world
At Meter, we're doing something very few teams can: applying frontier AI to reinvent how the internet itself is built, monitored, and managed.
We've achieved vertical integration of the entire enterprise networking stack: hardware, firmware, operating systems, and operations. This gives us full-stack visibility, the ability to control any part of the stack through a single API, a proprietary dataset no one else has, and a clear path to end-to-end automation. Plus, our systems already serve Fortune 500 companies, schools, factories, and cloud-scale clients.
Now, we're assembling a founding core engineering team to build and train models that understand these systems, optimize operations, anticipate failures, and repair issues before humans even notice them. In sum, building the decision layer to the infrastructure the modern world runs on.
You'll work directly with our founders and help define the future of one of the most impactful applications of models today.
See more at meter.ai.
Why this role is rare
  • Core ground floor impact: You won't be joining a large org with a fixed roadmap, you'll shape the roadmap. You'll define modeling approaches, team culture, and long-term vision alongside our executive team.
  • Real-world systems + frontier AI: This isn't chatbot optimization. You'll be building models that power fundamental infrastructure end-to-end, where reliability, accuracy, and latency really matter.
  • Unmatched data advantage, control over the full-stack: Meter owns the network from physical cables to packet-level telemetry to logs. No vendor or lab has this kind of data or control.
  • Thousands of H100s at your disposal: We've secured compute to match our ambition.
  • End-to-end ownership: You'll ship models into production networks, collaborate with firmware and application teams sitting next to you, and rapidly iterate in the wild.
  • Backed by the best: Investors include Sequoia, Sam Altman, Microsoft, and more. We're past product-market fit and entering scale.
What you might work on
  • Train end-to-end models, applied to fault prediction, network state modeling, and autonomous repair.
  • Build multi-modal over structured networking data, performing function-calling to make all decisions on a network .
  • Evaluate model performance over real-world hardware and virtualized environments.
You'll thrive here if you
  • Have built, trained, and scaled neural networks from the ground up.
  • Think in systems, not just benchmarks.
  • Are excited to model the physical world and collaborate across the hardware and software stack.
  • Want to build the technical DNA of a new applied research org from the ground up.

Apply