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Chatbot Training Jobs in Seattle, WA (NOW HIRING)

Manager, AI

Seatac, WA · On-site

$149K - $224K/yr

Oversee the full AI/ML software development lifecycle, ensuring best practices in model training ... Experience in developing enterprise-level GenAI applications, including chatbot development ...

Manager, AI

Seatac, WA

$149K - $224K/yr

Oversee the full AI/ML software development lifecycle, ensuring best practices in model training ... Experience in developing enterprise-level GenAI applications, including chatbot development ...

Manager, AI

Seattle, WA

$149K - $224K/yr

Oversee the full AI/ML software development lifecycle, ensuring best practices in model training ... Experience in developing enterprise-level GenAI applications, including chatbot development ...

... 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

See Seattle, WA salary details

$34.7K

$78.1K

$131.4K

How much do chatbot training jobs pay per year?

As of Aug 5, 2026, the average yearly pay for chatbot training in Seattle, WA is $78,088.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,200.00 and $84,800.00 per year, depending on experience, location, and employer.

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.
Infographic showing various Chatbot Training job openings in Seattle, WA as of July 2026, with employment types broken down into 1% Locum Tenens, 47% As Needed, 18% Full Time, 4% Part Time, 29% Nights, and 1% Summer. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $78,088 per year, or $37.5 per hour.

Software Engineer - Global E-Commerce AI Search Infrastructure (TikTok Shop)

TikTok

Seattle, WA • On-site

$148K - $300K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 5 days ago


TikTok rating

8.2

Company rating: 8.2 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

106th of 242 rated software companies


Job description

Responsibilities
We're building the next-generation AI search and shopping assistant for TikTok Shop, TikTok's global commerce platform, - powering Q&A cards, in-app chatbot, and visual search experiences that help billions of users discover products, explore stores, and shop through natural conversation. Our team owns the full search stack: from retrieval and ranking to multi-agent LLM engines, post-training infrastructure, and personalized memory. We translate cutting-edge research into production systems at global scale, with a focus on relevance, latency, and fast algorithm iteration. Responsibilities: - Build AI Search Agents: Design and ship ReAct-based agents with planning, memory, and tool use; implement DAG workflows and RAG pipelines for multi-turn shopping assistance and query understanding. Own the unified Agent Harness across Q&A cards, in-app chatbot, and visual search surfaces - with MCP tool-chain integration and end-to-end A/B support. - Improve LLM Query Understanding: Drive multi-turn conversation, cross-lingual analysis, and LLM reasoning chains for accurate, trustworthy search results; optimize answer generation pipelines (quantization, KV cache, continuous batching) for quality and latency. - Build Personalized Memory Infrastructure: Design high-throughput storage and retrieval for long-term user profiles and real-time memory (MemAgent); build near-real-time feature pipelines over billion-scale behavior sequences for low-latency serving of personalized signals. - Contribute to Training and Inference Infrastructure: Collaborate on post-training pipelines (SFT, RL, distillation) and model-serving infrastructure (tensor parallelism, speculative decoding, PD separation) to accelerate experimentation and hit latency targets. - Ship Research to Production: Bridge research and engineering - partner with algorithm teams to evaluate agent and LLM innovations, accelerate adoption, and ensure new capabilities land stably in production at scale.
Qualifications
Minimum Qualification(s): - Bachelor's or Master's in Computer Science, Computer Engineering, or a related technical field. - At least 3 years of industry experience building large-scale distributed systems, search infrastructure, or low-latency online services. - Proficiency in C++, Go, or Java (C++ preferred); strong systems fundamentals - data structures, OS, networking, multithreading, and Linux performance tuning. - Solid grasp of LLM and agent technologies - RAG, tool use, and multi-turn reasoning - with a track record of contributing to production AI systems. - Excellent system design instincts; able to independently architect and ship reliable, high-performance services; strong communication and ownership. Preferred Qualification(s): - Background in large-scale search, recommendation, advertising, or personalization systems - particularly e-commerce search at 100M+ user scale. - Experience shipping agentic systems or RAG pipelines in production - ReAct, tool calling, DAG orchestration, or MCP integrations. - Familiarity with LLM inference optimization - quantization, KV cache, speculative decoding, tensor parallelism - or hands-on experience with vLLM, TensorRT-LLM, or SGLang. - Experience with post-training workflows: SFT, RL (RLHF / PPO / GRPO), distillation, or reward model design. - Research publications at NeurIPS, ICML, ACL, CVPR, RecSys, or OSDI.
Job Information
[For Pay Transparency]Compensation Description (Annually)
The base salary range for this position in the selected city is $148200 - $300960 annually.
Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.
Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
For Los Angeles County (unincorporated) Candidates:
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:
1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
3. Exercising sound judgment.
About TikTok
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
Why Join Us
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.
We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.
Diversity & Inclusion
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.
TikTok Accommodation
TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at

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