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Chatbot Training Jobs in California (NOW HIRING)

Cerebras

Detection Engineer

San Francisco, CA · On-site

$150 - $200/hr

We aren't just "bolting on" a chatbot; we are architecting a constellation of high-precision AI ... training sets to harden the system against the next iteration of an attack. If you're ready to ...

Eltropy Inc.

Solutions Engineer

Santa Clara, CA · Remote

$140K - $160K/yr

Provide technical training and support to customers and internal teams, as required. * Continuously ... chatbot technology - all integrated in a single platform bolstered by AI, skill-based routing and ...

Spellbrush

AI Anime Researcher - LLM

San Francisco, CA · On-site

Think MiSide with LLMs, but truly integrated with gameplay, not just a RP chatbot. About Us Here at ... Bonus if your post training work is focused on roleplay. Bonus if you have worked on latency ...

Spellbrush

AI Anime Researcher - LLM

San Francisco, CA · On-site

Think MiSide with LLMs, but truly integrated with gameplay, not just a RP chatbot. About Us Here at ... Bonus if your post training work is focused on roleplay. Bonus if you have worked on latency ...

Pragmatike

Member of ML Technical Staff

San Francisco, CA · On-site

$200K - $350K/yr

Building RAG or chatbot applications without working on the underlying models. * Prompt engineering without model training experience. * Working exclusively in large, highly structured engineering ...

Tata Consultancy Service Limited

Product Owner

Irvine, CA · On-site

$120K - $150K/yr

... Assist / chatbot layer (if applicable) • Email / notifications / manager tools • Ensure a ... Commuter Benefits & Certification & Training Reimbursement. • Time Off: Vacation, Time Off, Sick ...

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All JobsChatbot Training JobsChatbot Training Jobs in California

Chatbot Training information

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 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 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 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 popular job titles related to Chatbot Training jobs in California?

For Chatbot Training jobs in California, the most frequently searched job titles are:

What job categories do people searching Chatbot Training jobs in California look for?

The top searched job categories for Chatbot Training jobs in California are:

What cities in California are hiring for Chatbot Training jobs?

Cities in California with the most Chatbot Training job openings:

Chatbot Training jobs near you
Infographic showing various Chatbot Training job openings in California as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, and 3% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution.

Detection Engineer

Cerebras

San Francisco, CA • On-site

$150 - $200/hr

Other

Posted 20 days ago

Key responsibilities

  • Design and build high-precision AI agents that collaborate to identify emerging threat patterns in live data.

  • Identify gaps in telemetry related to LLM-backed attackers and evolve detection agents to address them.

  • Develop pipelines for monitoring large-scale threat data in real-time and implement feedback loops to improve detection systems.

Job description

We are a team of ex-Google engineers who built the world’s largest defensive moats: Safe Browsing (5B+ users) and reCAPTCHA (5M+ sites). We’ve seen how global-scale detection works—and we know why it’s about to break.

The "traditional" detection stack—YARA rules, static signatures, and rigid heuristics—is failing. Adversaries are now using LLMs to automate polymorphism, crafting high-evasion, tailored payloads that bypass legacy systems by design.

We’re in stealth, building an Autonomous Detection Layer designed to fight AI with AI. We aren't just "bolting on" a chatbot; we are architecting a constellation of high-precision AI agents that hunt, triages, and neutralize threats in real-time.

Your Role: Detection Architect & Adversarial Lead

You won't just be writing detections; you'll be building the engines that generate them.

  • Architect Multi-Agent Systems: Design high-precision AI agents that collaborate to identify emerging threat patterns in live data.
  • Live in the Signal: You’ll be deep in the telemetry, identifying where LLM-backed attackers are finding gaps and evolving your agents to close them before the next campaign hits.
  • Rapid Prototyping: Move from "Zero-Day discovery" to "Automated Mitigation" in hours, not months. Our orchestration layer is built for engineers who think in OODA loops.
Why This is a Tier-1 Challenge
  • Zero-Day Velocity: The models change weekly. The bypass techniques change daily. Your detections must be adaptive, not reactive.
  • The Adversary is Competent: We are fighting sophisticated actors using AI to automate social engineering, credential stuffing, and evasive malware.
  • No Legacy Bloat: No 20-minute CI/CD pipelines. No "Change Management" boards for a logic tweak. You own the stack.
Who You Are
  • Adversarial Mindset: You understand how to bypass EDR/WAFs and use that knowledge to build better ones. You think in terms of TTPs, not just IOCs.
  • Data-Fluent: You have 2–10 years of experience and are comfortable at the intersection of security telemetry (logs, PCAPs, behavioral traces) and ML/AI systems.
  • Execution-First: You value high-signal alerts and low false-positive rates. You’d rather ship a 90% solution today than a 100% solution next quarter.
The Stats
  • The Pedigree: Founders are 3x founders with 30+ years of combined AI/Security experience at Google (Top 1% Engineering).
  • The Scale: We’ve previously protected billions. We’re doing it again for a $5B+ market that is currently defenseless against AI-driven threats.
  • The Speed: Flat hierarchy. Direct ownership. We move at the speed of the battlefield.

AI is only as good as the signal it consumes. As a Detection Infra lead, you’ll build the "Sensors and Synapses" of our platform:

  • Internet-Scale Ingestion: Build pipelines to monitor billions of events and petabytes of threat data in real-time.
  • Agent Orchestration: Design the infra that fine-tunes models on the fly using fresh adversarial data and manages GPU workloads across distributed clusters.
  • Feedback Loops: Implement the "Closed Loop" system where detections from the wild are instantly fed back into training sets to harden the system against the next iteration of an attack.

If you’re ready to build the tech that defines the next decade of cyber defense, let’s talk.

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