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Ai Human Feedback Jobs (NOW HIRING)

Gen AI Engineer

Plano, TX · On-site

$40 - $50/hr

Familiar with AWS AI/ML services (e.g., SageMaker, Bedrock, Comprehend, Lex) is a PLUS * AWS AI ... Implement prompt engineering, instruction tuning, and reinforcement learning from human feedback ...

Lead Gen AI Engineer

Plano, TX · On-site

$85 - $110/hr

Familiarity with AWS AI/ML services (e.g., SageMaker, Bedrock, Comprehend, Lex) * AWS AI ... Implement prompt engineering, instruction tuning, and reinforcement learning from human feedback ...

Marketing Expert

$80 - $150/hr

Prior experience with AI evaluation, data annotation, human-feedback projects, or AI model training is preferred but not required. * Comfortable working independently while collaborating effectively ...

Data Science Expert

$120 - $170/hr

Experience contributing to AI evaluation, model training, human feedback, or data annotation initiatives. * Familiarity with large language models (LLMs), AI-assisted analytics, or machine learning ...

AI/LLM Engineer

San Francisco, CA · On-site

$90K - $200K/yr

This is a high-impact, full-stack AI engineering role where you'll own end-to-end delivery of ... Apply RLHF and DPO techniques to align LLMs with human feedback * Build robust data pipelines to ...

As a Staff R&D AI Engineer, you will lead the development of cutting-edge AI systems that bridge ... Implement RLHF (Reinforcement Learning from Human Feedback) systems to improve model alignment and ...

Previous experience with AI model evaluation, human feedback projects, or AI training initiatives. * Experience developing consulting methodologies, quality frameworks, or internal knowledge ...

Analyze employee feedback and engagement data to identify improvement opportunities * Design ... Increased adoption of AI-enabled HR capabilities * Improved HR operational efficiency and employee ...

Senior HR Business Partner

Newark, NJ · On-site

$120 - $180/hr

Analyze employee feedback and engagement data to identify improvement opportunities * Design ... Increased adoption of AI-enabled HR capabilities * Improved HR operational efficiency and employee ...

Analyze employee feedback and engagement data to identify improvement opportunities * Design ... Increased adoption of AI-enabled HR capabilities * Improved HR operational efficiency and employee ...

Showing results 21-40

Ai Human Feedback information

See salary details

$26.5K

$44.2K

$60K

How much do ai human feedback jobs pay per year?

As of Aug 8, 2026, the average yearly pay for ai human feedback in the United States is $44,245.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,500.00 and $48,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI human feedback specialist?

To thrive as an AI Human Feedback Specialist, you need a solid understanding of language, critical thinking, and attention to detail, often supported by a background in linguistics, communication, or a related field. Familiarity with annotation tools, feedback platforms, and sometimes basic programming or data analysis skills is typically required. Strong written communication, analytical thinking, and the ability to provide constructive, unbiased feedback are essential soft skills. These competencies ensure the accuracy, fairness, and effectiveness of AI systems by enabling clear and high-quality human evaluation.

What is an AI human feedback?

An AI Human Feedback job involves evaluating and providing feedback on the outputs generated by artificial intelligence models. People in these roles assess the accuracy, relevance, and appropriateness of AI responses, helping improve their performance and reliability. This work is essential for training, testing, and refining AI systems to ensure they align with human expectations and ethical guidelines. AI Human Feedback roles can include tasks like rating chatbot answers, annotating data, and identifying biases or errors in AI-generated content.

What is the difference between Ai Human Feedback vs Data Annotator?

AspectAi Human FeedbackData Annotator
Required CredentialsBasic technical skills, sometimes certifications in AI or data labelingMinimal formal education, training often provided on the job
Work EnvironmentRemote or office-based, collaborative with AI teamsPrimarily remote or on-site data labeling tasks
Industry UsageAI development, machine learning projectsData preparation for AI, machine learning, and analytics
Search & Comparison IntentUnderstanding roles in AI feedback processesData labeling and annotation tasks for AI training

Ai Human Feedback involves providing insights to improve AI models, often requiring some technical understanding. Data Annotators focus on labeling data to train AI systems, typically with minimal formal credentials. Both roles are essential in AI development but differ in scope and technical requirements.

What are some typical challenges faced by professionals in AI human feedback roles and how can they be addressed?

Professionals in AI human feedback roles often encounter challenges such as ensuring consistency and objectivity when evaluating AI outputs, managing large volumes of data, and staying updated with evolving AI technologies. It’s important to develop clear guidelines and maintain open communication with team members to align on evaluation standards. Regular training sessions and peer reviews can help enhance accuracy and address potential biases, fostering a collaborative and supportive work environment.
More about Ai Human Feedback jobs
What cities are hiring for Ai Human Feedback jobs? Cities with the most Ai Human Feedback job openings:
What states have the most Ai Human Feedback jobs? States with the most job openings for Ai Human Feedback jobs include:
What job categories do people searching Ai Human Feedback jobs look for? The top searched job categories for Ai Human Feedback jobs are:
Infographic showing various Ai Human Feedback job openings in the United States as of August 2026, with employment types broken down into 83% Full Time, 15% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $44,245 per year, or $21.3 per hour.

Senior Machine Learning Engineer

Retell AI

San Francisco, CA • On-site

$225K - $325K/yr

Full-time

Medical, Dental, Vision

Posted 4 days ago


Job description

ABOUT RETELL AI
Retell AI is using first-principles thinking to reimagine the call center with cutting-edge voice AI. Thousands of companies now use Retell's AI voice agents to handle sales, support, and logistics calls that once required large teams of human agents. Backed by Y Combinator, Alt Capital, and other leading investors, we've scaled to $80M in ARR with a team of 50, up from $5M at the start of 2025, and are now valued at over $1.5B.
Our vision for 2026 is to build a modern CX platform where entire contact centers are powered by AI. Instead of basic automation that needs constant human tuning, we're creating intelligent AI "workers" that act as frontline agents, QA analysts, and managers, continuously executing, monitoring, and improving every customer interaction.
We're growing fast and looking for ambitious builders who want to tackle hard technical problems, move quickly, and have a real impact on one of the fastest-growing voice AI companies in the world.
Let's build the future together.
Recent recognition:
  • No. 1 Best Places to Work in the Bay Area, San Francisco Business Times 2026
  • Top 50 AI Apps, a16z (2025)
  • #3 Fastest-Growing Software Company, G2 Best Software Awards 2026
  • Best Agentic AI Software, G2 Best Software Awards 2026
  • #4 Fastest-Growing Software Vendor, Brex Benchmark 2025
  • Enterprise Tech 30 Class of 2026, Nasdaq & Wing VC
  • Top-Ranked Startup, Lean AI Leaderboard
  • Backed by Y Combinator

ABOUT THE ROLE
Retell AI transforms customer experience with voice AI for enterprises, including customers like CVS/Aetna, American Airlines, Lenovo, and Grab. We have more customer stories than we can tell!
This is a hands-on, high-ownership role for ML engineers who want to build production models that actually ship, and perform under real-world constraints. As a Founding Senior Machine Learning Engineer at Retell, you'll work across the ML stack to power human-like voice agents that handle millions of real-time phone conversations.
You'll fine-tune large language models and audio models, evaluate them with rigorous benchmarks (and human feedback), and deploy them into latency-sensitive, high-traffic systems. You'll own model performance end-to-end-from training pipelines to post-deployment monitoring-and shape our ML strategy alongside the founding team.
If you're excited by hard technical challenges, fast iteration, and the opportunity to define how voice AI works at scale, this role is a rare chance to do it from the ground up.
KEY RESPONSIBILITIES
  • Train & Tune Models - Fine-tune LLMs and audio models to maximize speed, accuracy, and production-readiness-pushing the frontier of real-time AI voice experiences.
  • Benchmark & Evaluate - Build datasets, define rigorous metrics, and measure model performance across high-impact voice AI tasks to guide development.
  • Deploy to Production - Work closely with engineering to ship models, monitor them in the wild, and ensure they stay fast, reliable, and accurate at scale.
  • Run Human Evaluations - Build scalable pipelines to collect structured human feedback, benchmark subjective quality, and inform model iterations.
  • Level Up Infrastructure - Design and maintain the ML infrastructure needed for fast experimentation, robust training, and continuous deployment.

YOU MIGHT THRIVE IF YOU
  • ML Engineer with Real-World Experience - You've trained and shipped models in production. Bonus if you've worked with LLMs or audio models.
  • Fluent in Modern ML Stack - You know your way around Python, PyTorch, and today's ML tools-from training pipelines to evaluation benchmarks.
  • Execution-Oriented - You move fast, take ownership, and focus on solving real problems over perfect ones.
  • Startup-Ready - You're adaptable, resilient, and energized by ambiguity and fast-changing priorities.
  • Clear Communicator & Team Player - You collaborate well across functions and push decisions forward.

JOB DETAILS
  • Cash: $225,000 - $325,000 base salary
  • Equity: Offers Equity
  • Location: Redwood City, CA, US
  • US Visas: Retell AI is open to sponsoring work authorization for qualified candidates, including H1B/H-1B, TN, L-1, E-3, F-1 (OPT/CPT), and O-1 visas.

OTHER BENEFITS
  • 100% coverage for medical, dental, and vision insurance
  • $70/day DoorDash credit for unlimited breakfast, lunch, dinner, and snacks
  • $200/month wellness reimbursement (gym, fitness classes, etc.)
  • $300/month commuter reimbursement (gas, Caltrain, etc.)
  • $75/month phone bill reimbursement
  • $50/month internet reimbursement

COMPENSATION PHILOSOPHY
  • Best Offer Upfront: Choose from three cash-equity balance options, no negotiation needed.
  • Top 1% Talent: Above-market pay (top 5 percentile) to attract high performers.
  • High Ownership: Small teams, >$1M revenue/employee, and significant equity.
  • Performance-Based: Offers tied to interview performance, not experience or past salaries.

INTERVIEW PROCESS
  • Talent Screen (15min): chat with our recruiter to get a better sense of the role, the team, and what it's like to work here.
  • Technical Interview (45 min): MLE coding
  • Technical Interview (45 min): ML questions deepdive
  • Onsite/Virtual Interviews (3 hrs): Hosted in our office if located in the Bay Area or virtual, with three rounds:
    1. ML System Design: A non-coding interview focused on whiteboarding and high-level system architecture.
    2. ML Question Deep Dive: In-depth discussion exploring your approach to a machine learning problem.
    3. Backend + AI Practical: A hands-on coding interview combining backend development with AI integration.

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