AI Trainer Jobs
Shape Tomorrow's AI.

AI trainers help improve AI models through several methods. RLHF (Reinforcement Learning from Human Feedback) specialists rate and rank AI responses to teach models what 'good' looks like. Data annotators label training data for specific domains like code, medical, or legal content. Quality assurance reviewers audit other trainers' work and establish guidelines. Red teamers test AI systems for harmful outputs. The best-paid roles combine domain expertise (coding, medicine, law) with understanding of AI training principles.

Compensation varies dramatically by role type and expertise. Entry-level annotation through platforms like Remotasks or Outlier: $15-30/hr (contractor). Specialized domain trainers (coding, math, science): $40-80/hr or $80K-$120K full-time. Senior RLHF specialists at major labs: $120K-$180K+ full-time with benefits. Technical roles requiring coding skills (writing code for AI to learn from) pay the highest. Full-time positions at Anthropic, OpenAI, or Scale AI include equity that can significantly increase total compensation.

Major employers include: Scale AI (largest AI training workforce, both contractors and FTEs), Anthropic (high-quality RLHF roles, strong culture fit emphasis), OpenAI (competitive roles, often require technical background), Google DeepMind (research-oriented training roles), Surge AI, Labelbox, and Appen (various specializations). Many hire through contractor platforms first, then convert top performers to full-time. Direct applications to AI labs typically require stronger credentials but offer better compensation and career growth.

Core skills: Strong written communication, attention to detail, ability to follow complex guidelines consistently. Valuable specializations: Coding ability (Python, JavaScript) for code training roles, STEM background for math/science training, writing expertise for content quality roles, subject matter expertise in law, medicine, or finance. Differentiators: Understanding of how LLMs work, experience with prompt engineering, ability to articulate reasoning clearly. For top roles: Graduate degrees help but aren't required if you can demonstrate expertise.

Yes, but it requires intentional positioning. Path 1: Trainer to QA Lead to Training Program Manager ($150K+). Path 2: Domain specialist to AI Product roles (use training insights to inform product decisions). Path 3: Technical trainer to ML Engineer (if you develop coding skills alongside). Path 4: Policy/red team specialist to AI Safety roles at major labs. The key is treating training work as skill-building, not just task completion. Document your contributions, learn the underlying ML concepts, and network within the AI community.

Most AI training roles are fully remote, which is both an opportunity and a challenge. Opportunity: Access to global job market regardless of location. Challenge: High competition, especially for entry-level roles. Many companies hire trainers across time zones for 24/7 coverage. Some senior roles at major labs (Anthropic, OpenAI) may prefer or require Bay Area presence, but this is changing. Contractor roles offer maximum flexibility but less stability. Full-time remote positions typically still require US work authorization for major AI labs.

Not necessarily. While some programming experience is helpful, many of my clients have successfully transitioned from web development, data science, or other technical backgrounds. We'll assess your current skills during our strategy call and create a personalized plan that meets you where you are.

Most clients invest 10-15 hours per week, but this can be flexible based on your schedule. We'll have weekly 1:1 calls plus time for you to work on projects and learning. The key is consistency. Regular, focused effort beats occasional marathons.

You become a member of the AI Native Engineer community, and you stay and keep going. Career transitions take different amounts of time for everyone, and I'm not going to abandon you if things take longer. You get ongoing support through good times and bad.

Online courses give you content. 1:1 coaching gives you a personalized roadmap, direct feedback on your work, career strategy, interview prep, and accountability. You get answers to your specific questions and guidance tailored to your unique situation instead of generic advice meant for everyone.

Investment details are discussed during the 30-minute strategy call, where we'll assess your goals and create a custom plan. The program is designed to pay for itself quickly through your increased salary. Most AI engineers see a 20-50% pay increase.

Absolutely. Most of my clients work full-time and make steady progress. We'll schedule calls at times that work for you and create a realistic plan that fits your schedule. Consistency matters more than intensity.