AI Data Trainer Jobs
AI Data Trainer jobs are open across technology, e-commerce, healthcare, and research sectors, from entry-level annotator roles to senior trainers and team leads, with specializations in natural language processing, computer vision, and reinforcement learning from human feedback. See the openings below and apply to the ones that match your experience.
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Karman Space & Defense is a leader in the rapid design, development, and production of critical, next-generation system solutions that align with the U.S. Department of War and its allies' core mission priorities, and meet the accelerating demand for access to space. Building on nearly 50 years of success, we deliver Payload & Protection Systems, Aero/Hydrodynamic Interstage Systems, and Propulsion & Launch Systems to more than 80 prime contractors supporting over 130 space and defense programs.
In this senior individual‑contributor role, you will translate Karman's enterprise artificial intelligence (AI) strategy into secure, scalable, and reusable architectures that accelerate responsible adoption across the organization. You will shape technical patterns, build reference implementations, evaluate emerging technologies, and establish guardrails that enable governed self‑service. Partnering closely with AI/Data & Automation, Business Systems, Cybersecurity, Infrastructure, and functional teams, you will provide hands‑on technical leadership that strengthens solution quality, operational consistency, and enterprise readiness.
Responsibilities
- Defines and evolves Karman's enterprise AI reference architecture.
- Establishes architectural patterns for model access, retrieval‑augmented generation (RAG), orchestration, agents, application programming interfaces (APIs), evaluation, observability, and cost management.
- Develops technical standards for Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI, Microsoft Fabric, and other approved enterprise AI capabilities.
- Evaluates external platforms and models based on security, performance, cost, and business needs.
- Designs architectures that support portability using APIs, abstraction layers, open protocols, and exit strategies.
- Builds proofs of concept, reference implementations, reusable components, and technical accelerators.
- Provides hands‑on support for complex AI use cases, including RAG solutions, agentic workflows, model‑integrated applications, and automation.
- Establishes reusable templates, patterns, guardrails, and documentation to enable governed self‑service.
- Translates enterprise AI governance requirements into technical controls for identity, access, logging, monitoring, classification, retention, and human oversight.
- Defines evaluation, observability, quality, operational readiness, incident response, and lifecycle management standards for AI solutions.
Required Qualifications
- Significant experience in enterprise architecture, cloud architecture, software engineering, or platform engineering.
- Recent experience designing and deploying production generative artificial intelligence (AI) solutions.
- Strong working knowledge of the Microsoft cloud and AI ecosystem, including Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI, Microsoft Fabric, Entra ID, Purview, and Microsoft security technologies.
- Hands‑on experience integrating commercial AI models through APIs and building model‑enabled applications.
- Strong understanding of RAG architectures, agent patterns, tool use, model orchestration, vector search, and enterprise data integration.
- Familiarity with standards and technologies such as Model Context Protocol (MCP), OpenTelemetry, open‑weight models, and modern inference platforms.
- Experience designing secure systems in regulated or high‑assurance environments.
- Ability and willingness to write code, build prototypes, review designs, and troubleshoot technical issues.
- Strong written and verbal communication skills with the ability to explain complex technical tradeoffs to technical and executive audiences.
Preferred Qualifications
- Experience in aerospace, defense, government, manufacturing, financial services, or other regulated industries.
- Experience with GCC High, sovereign cloud, restricted environments, or controlled‑data architectures.
- Familiarity with frameworks such as Cybersecurity Maturity Model Certification (CMMC), National Institute of Standards and Technology (NIST) Special Publication 800‑171, Controlled Unclassified Information (CUI), International Traffic in Arms Regulations (ITAR), NIST AI Risk Management Framework (RMF), and International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 42001.
- Experience integrating AI with enterprise platforms such as enterprise resource planning (ERP), product lifecycle management (PLM), manufacturing execution systems (MES), customer relationship management (CRM), productivity, analytics, and workflow systems.
- Familiarity with graphics processing unit (GPU) infrastructure, self‑hosted models, fine‑tuning, and private inference environments.
- Relevant Microsoft, cloud, architecture, or security certifications.
This position requires U.S. person status under U.S. export control laws, including U.S. citizens and nationals, lawful permanent residents, refugees, and asylees.
Benefits
- Medical, dental, and vision insurance
- 401(k) with company match
- Paid time off
- Health Savings Account (HSA) with company contribution
- Flexible Spending Accounts (FSA)
- Company‑paid life and ADdummyamp;D insurance
- Short‑ and long‑term disability coverage
- Tuition reimbursement
Karman Space and Defense is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, protected veteran status, or any other status protected by applicable federal, state, or local law.
View our Privacy Policy
Karman Space & Defense is a leader in the rapid design, development, and production of critical, next-generation system solutions that align with the U.S. Department of War and its allies' core mission priorities, and meet the accelerating demand for access to space. Building on nearly 50 years of success, we deliver Payload & Protection Systems, Aero/Hydrodynamic Interstage Systems, and Propulsion & Launch Systems to more than 80 prime contractors supporting over 130 space and defense programs.
In this senior individual‑contributor role, you will translate Karman's enterprise artificial intelligence (AI) strategy into secure, scalable, and reusable architectures that accelerate responsible adoption across the organization. You will shape technical patterns, build reference implementations, evaluate emerging technologies, and establish guardrails that enable governed self‑service. Partnering closely with AI/Data & Automation, Business Systems, Cybersecurity, Infrastructure, and functional teams, you will provide hands‑on technical leadership that strengthens solution quality, operational consistency, and enterprise readiness.
Responsibilities
- Defines and evolves Karman's enterprise AI reference architecture.
- Establishes architectural patterns for model access, retrieval‑augmented generation (RAG), orchestration, agents, application programming interfaces (APIs), evaluation, observability, and cost management.
- Develops technical standards for Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI, Microsoft Fabric, and other approved enterprise AI capabilities.
- Evaluates external platforms and models based on security, performance, cost, and business needs.
- Designs architectures that support portability using APIs, abstraction layers, open protocols, and exit strategies.
- Builds proofs of concept, reference implementations, reusable components, and technical accelerators.
- Provides hands‑on support for complex AI use cases, including RAG solutions, agentic workflows, model‑integrated applications, and automation.
- Establishes reusable templates, patterns, guardrails, and documentation to enable governed self‑service.
- Translates enterprise AI governance requirements into technical controls for identity, access, logging, monitoring, classification, retention, and human oversight.
- Defines evaluation, observability, quality, operational readiness, incident response, and lifecycle management standards for AI solutions.
Required Qualifications
- Significant experience in enterprise architecture, cloud architecture, software engineering, or platform engineering.
- Recent experience designing and deploying production generative artificial intelligence (AI) solutions.
- Strong working knowledge of the Microsoft cloud and AI ecosystem, including Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI, Microsoft Fabric, Entra ID, Purview, and Microsoft security technologies.
- Hands‑on experience integrating commercial AI models through APIs and building model‑enabled applications.
- Strong understanding of RAG architectures, agent patterns, tool use, model orchestration, vector search, and enterprise data integration.
- Familiarity with standards and technologies such as Model Context Protocol (MCP), OpenTelemetry, open‑weight models, and modern inference platforms.
- Experience designing secure systems in regulated or high‑assurance environments.
- Ability and willingness to write code, build prototypes, review designs, and troubleshoot technical issues.
- Strong written and verbal communication skills with the ability to explain complex technical tradeoffs to technical and executive audiences.
Preferred Qualifications
- Experience in aerospace, defense, government, manufacturing, financial services, or other regulated industries.
- Experience with GCC High, sovereign cloud, restricted environments, or controlled‑data architectures.
- Familiarity with frameworks such as Cybersecurity Maturity Model Certification (CMMC), National Institute of Standards and Technology (NIST) Special Publication 800‑171, Controlled Unclassified Information (CUI), International Traffic in Arms Regulations (ITAR), NIST AI Risk Management Framework (RMF), and International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 42001.
- Experience integrating AI with enterprise platforms such as enterprise resource planning (ERP), product lifecycle management (PLM), manufacturing execution systems (MES), customer relationship management (CRM), productivity, analytics, and workflow systems.
- Familiarity with graphics processing unit (GPU) infrastructure, self‑hosted models, fine‑tuning, and private inference environments.
- Relevant Microsoft, cloud, architecture, or security certifications.
This position requires U.S. person status under U.S. export control laws, including U.S. citizens and nationals, lawful permanent residents, refugees, and asylees.
Benefits
- Medical, dental, and vision insurance
- 401(k) with company match
- Paid time off
- Health Savings Account (HSA) with company contribution
- Flexible Spending Accounts (FSA)
- Company‑paid life and ADdummyamp;D insurance
- Short‑ and long‑term disability coverage
- Tuition reimbursement
Karman Space and Defense is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, protected veteran status, or any other status protected by applicable federal, state, or local law.
View our Privacy Policy
AI Data Trainer Jobs by Experience Level
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Find AI Data Trainer JobsAI Data Trainer Job Market
Who's Hiring
- Booz Allen Hamilton20
- JPMorganChase11
- Johns Hopkins University Applied Physics Laboratory9
- University of San Diego6
- Penn State University4
Top Industries Hiring
- Education
- Technology & Software
- Banking & Financial Services
- Healthcare & Medical Services
- Insurance
What Employers Look For
The qualifications that appear most often in AI data trainer jobs.
- Native or near-native fluency in English with strong written communication skills
- Experience with data annotation tools or labeling platforms for text, image, or audio
- Ability to follow detailed annotation guidelines and style guides with high accuracy
- Bachelor's degree in linguistics, computer science, a related field, or equivalent experience
- Familiarity with large language model outputs and prompt-response evaluation tasks
- Strong attention to detail and ability to maintain consistent quality across repetitive tasks
Tips for Your AI Data Trainer Job Search
Tailor your resume for annotation work
Highlight specific annotation tasks you've completed, such as labeling bounding boxes, ranking model outputs, or writing prompt-response pairs. Recruiters scan for task types and data modalities, not just job titles, so name the exact formats you've worked with.
Show your quality and consistency scores
Many ai data trainer roles use inter-annotator agreement metrics to evaluate contributors. If you've maintained high accuracy or agreement scores on a previous project, include that in your resume or cover letter as a concrete performance signal.
Target postings that name the task type
Filter openings by the data type you know best, whether that's text, audio, image, or video annotation. A posting that specifies 'RLHF' or 'multimodal labeling' tells you exactly what pipeline you'd join, so you can write a tighter application.
Apply early to roles that fit
Migrate Mate lists ai data trainer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare for a paid annotation trial
Many employers screen candidates with a short paid task before the formal interview, asking you to label a sample dataset or evaluate model outputs. Practice following detailed annotation guidelines precisely, because speed matters less than consistency and adherence to instructions.
Negotiate scope before accepting contract work
AI data trainer roles often start as hourly contracts with no guaranteed hours. Before accepting, ask about minimum weekly hours, task availability, and whether full-time conversion is possible, so you're not surprised by inconsistent workloads after you've committed.
AI Data Trainer Jobs: Frequently Asked Questions
Which companies are hiring the most ai data trainers?
Booz Allen Hamilton, JPMorganChase, and Johns Hopkins University Applied Physics Laboratory are hiring the most ai data trainers right now, with openings concentrated in Virginia, California, and Texas, based on current listings on Migrate Mate as of November 2026. Demand is highest at AI labs, large technology companies, and specialized data annotation firms supporting model development pipelines.
How many ai data trainer jobs are remote?
About 55% of ai data trainer openings are fully remote or hybrid as of November 2026, making it one of the more location-flexible roles in the technology sector. Text-based annotation and model evaluation tasks are the most likely to be fully remote, while roles involving physical hardware or in-person data collection tend to require on-site presence.
How do you become an ai data trainer?
Start by building hands-on experience with annotation work through freelance labeling projects or contributor programs that accept applicants without prior credentials. Practice reading and applying detailed annotation guidelines precisely, since consistency is the core skill employers test. Strengthen your resume by noting specific data types you've labeled, then target entry-level postings that offer structured onboarding and task variety.
Can you get hired as an ai data trainer with little or no experience?
Yes, many ai data trainer roles are designed as entry points and do not require prior annotation experience. Employers typically care more about written fluency, attention to detail, and the ability to follow complex instructions than formal credentials. Completing a short freelance annotation task or contributor assignment, even unpaid, gives you a concrete example to reference in applications and helps you pass screening trials.
What does the ai data trainer interview process look like?
Most ai data trainer hiring processes begin with an application review followed by a short screening call to assess communication skills and availability. Candidates then complete a paid or unpaid annotation trial where they label a sample dataset according to a provided style guide, and their accuracy and consistency scores are evaluated. Strong performers advance to a final interview or are extended an offer directly.
Where can I find and apply to ai data trainer jobs?
You can find and apply to ai data trainer jobs on Migrate Mate, which lists current openings from across the United States. Search for roles that match your experience and background, then apply directly to each listing that fits. The platform pulls openings from a range of employers, from large technology companies to specialized annotation firms, so you can compare opportunities in one place.
See All 300+ AI Data Trainer Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI Data Trainer Jobs