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AI Trainer - Freelance Annotator
Location
United States
Posted
1 day ago
Salary
$18 / hour
Seniority
Mid Level
No structured requirement data.
Job Description
AI Trainer - Freelance Annotator
Toloka Annotators
Role Description As an AI Trainer - Annotator, your contribution will help train AI models, shaping how they understand and interact with the world. This isn't just traditional feedback - you'll be evaluating and improving how AI reasons, responds, and handles real-world tasks like online shopping experiences. While each project involves unique tasks, contributors may: - Evaluate AI-generated responses across a range of tasks, including e-commerce and online shopping scenarios, drawing on your own experience as an online shopper. - Provide honest, detailed, and useful feedback that helps improve model and agent performance. - Follow style and quality standards to ensure consistency. - Collaborate with Quality Assurance Specialists to refine and improve content. Qualifications - Bachelor’s degree in any subject field. - At least 1 year of professional or educational experience in any field. - Strong written English (C1/C2). - Stable internet connection. Requirements - Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid. Benefits - Earn up to $18 per hour equivalent, depending on level and pace of contribution. - Compensation varies across projects depending on scope, complexity, and required expertise. - Other projects on the platform may offer different earning levels based on their requirements. Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.
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Data Architecture & Catalog Strategy - Lead the architectural design of enterprise data catalog programs - defining scope, platform selection criteria, governance operating models, and phased adoption roadmaps. - Advise on the strategic application of knowledge graph concepts, semantic technologies, and ontological frameworks (RDF, SPARQL) to enterprise data and AI use cases. - Shape data architecture principles and standards that underpin AI readiness - including data lineage, metadata quality, classification taxonomies, and access governance. - Translate complex data architecture requirements into clear, actionable designs that can be executed by delivery and technical teams. - Define success metrics and maturity benchmarks for data catalog programs, enabling customers to track progress and demonstrate value to executive stakeholders. AI Governance, Risk & Responsible AI - Define and embed AI governance frameworks covering data stewardship, model risk, bias controls, audit trails, and compliance postures. - Support customers in operationalize responsible AI practices aligned to regulatory requirements and internal policies. - Establish data governance frameworks that position metadata management, data stewardship, and knowledge graph capabilities as foundational trust layers for enterprise AI programs. - Guide customers in regulated industries on aligning data catalog and governance architectures to compliance and regulatory obligations, embedding controls into the design rather than as an afterthought. - Partner with AI Control Tower to establish monitoring, observability, and continuous optimization capabilities post-deployment. Adoption, Enablement & Change Management - Lead AI adoption strategies including readiness assessments, stakeholder engagement plans, AI literacy programmers, and change communications. - Define adoption KPIs and value realization metrics; track and report outcomes; provide consultative guidance for continuous optimization and expansion. - Coach customer teams to build internal AI capability, reducing dependency and accelerating long-term self-sufficiency. - Monitor adoption, usage, and value realization metrics post-deployment; provide recommendations for risk mitigation and growth. Practice Development & Thought Leadership - Collaborate cross-functionally with Sales, Solution Consulting, Customer Success, Platform, and Product teams to embed AI advisory across the customer lifecycle. - Build and maintain industry-specific AI advisory playbooks and frameworks - verticalized use-case catalogs, value models, governance templates, and deployment patterns - to support scalable, repeatable delivery. - Act as a thought-leader internally and externally: contribute to white papers, points-of-view, reference architectures, best-practice guides, and represent the organization at AI forums and customer briefings. - Support pre-sales by qualifying opportunities, shaping proposals, and presenting transformation vision to executive buyers. Qualifications To be successful in this role, you will have - Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. - 10+ years of experience in management consulting, enterprise architecture, or a senior technology advisory role, with a demonstrated focus on Artificial Intelligence, Machine Learning, or digital transformation at enterprise scale. - ServiceNow domain knowledge, including: Now Assist and Generative AI Skills / Skill Kit, AI Agents and Agentic workflows, AI Control Tower, Retrieval-Augmented Generation (RAG), Knowledge Graphs, Agent-to-Agent (A2A), and Model Context Protocol (MCP). - Proven track record designing and managing complex, multi-stakeholder AI or digital-transformation engagements - including use-case definition, business case development, integration, data strategy, governance, and operational adoption. - Strong understanding of enterprise data architecture, data quality, knowledge management, integrations, and compliance and regulatory frameworks. - Demonstrated ability to architect enterprise data catalog and metadata management strategies, with knowledge of platforms. - Excellent communication and interpersonal skills - ability to articulate technical and business value to C-level executives, align stakeholders, and influence strategic decision-making. - Experience working in fast-paced, dynamic environments with capability to manage ambiguity and tailor consulting deliverables to different customer maturity levels, from early adopters to AI-ready enterprises. - Working knowledge of knowledge graph principles, semantic technologies, and standards (RDF, SPARQL) as applied to enterprise data architecture. - Broad familiarity with the ServiceNow platform and modules (ITSM, CSM, FSM, HRSD, App Engine), ideally including implementation or architecture experience. ServiceNow certifications (Certified System Administrator, Certified Implementation Specialist, Certified Technical Architect) are desirable. - AI/ML certifications (e.g. AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, or equivalent) are desirable. - Background in one or more target industries - Financial Services, Healthcare, Public Sector, Manufacturing, or Retail - is highly desirable. For positions in this location, we offer a base pay of $173,200- $270,600, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.



