Use police dispatch and emergency communications expertise to help train and evaluate AI systems for high-stakes communication environments. This remote contract role offers flexible part-time work at $30–$55 per hour.
General Annotation
100% Remote Hourly · $30–$55/hr
$30–$55/hr
Compensation
Worldwide
Eligibility
Entry
Experience
Aug 12, 2026
Posted
Open worldwide
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About AI Training Work
AI training is the human side of building artificial intelligence. People with real-world expertise help prepare examples, evaluate model behavior, and provide feedback so AI systems can perform more accurately and reliably.
In this role, your emergency communications experience will contribute practical insight to AI training and evaluation in a high-stakes operational context.
The Role
OpenTrain AI is seeking a Police Dispatcher AI Training Specialist to apply practical police dispatch or emergency communications expertise to AI training work. You will process incident requests, follow established protocols, and provide accurate real-world input for model learning and evaluation.
This is a remote, part-time contractor opportunity for professionals who can make sound decisions while managing multiple communications and priorities. Prior AI experience is not required; domain knowledge in emergency communications is the central qualification.
Employment type: Contractor, part time
Time commitment: 20+ hours per week
Pay: $30–$55 per hour
Work location: Worldwide
Primary language: English
Experience level: Entry level AI-training opportunity; professional dispatch or emergency communications experience required
What You'll Do
You will use your knowledge of emergency communications to produce accurate, consistent, and operationally realistic input for AI systems.
Receive and process emergency requests and incidents through radio, phone, and digital communication channels.
Use standardized protocols and checklists to gather information, assess urgency, and maintain accurate records.
Triage concurrent requests while maintaining composure, professionalism, and attention to detail.
Coordinate and route requests to appropriate field resources and agencies according to established procedures.
Produce clear, concise written and verbal communications and reliable records.
Review protocols and provide feedback that supports improved operating procedures and AI training datasets.
Requirements
You should bring professional experience in police dispatch, emergency communications, or a comparable high-stakes coordination setting. The work requires reliable judgment, precise communication, and consistent use of established procedures.
Ability to triage concurrent requests and prioritize resources under pressure.
Strong multitasking, prioritization, and triage judgment.
Clear written and verbal communication during stressful or uncertain situations.
Experience applying standardized protocols or checklists consistently.
Familiarity with digital communication platforms and information management systems used in dispatch or emergency coordination.
Strong accuracy, attention to detail, and commitment to continuous improvement.
Ability to provide domain-specific insights for AI model learning and evaluation.
APCO or NENA certification where applicable.
Who Should Apply
This opportunity is suited to police dispatchers, emergency communications professionals, and others with comparable experience coordinating high-stakes incidents. You do not need a background in AI: practical expertise, disciplined protocol use, and the ability to communicate clearly are the key qualifications.
The flexible, remote structure can fit around other professional, educational, or personal commitments while allowing you to build experience in a fast-growing technology field.
Why Work With OpenTrain
OpenTrain gives you a place to build and manage your AI training career while applying specialized professional knowledge to cutting-edge systems. A stronger OpenTrain profile can help you show credible experience, discover relevant opportunities, and grow a durable portfolio of AI training and data-labeling work.
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