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Commission Rlhf Jobs (NOW HIRING)

Apple

Algorithm Evaluation Manager

Sunnyvale, CA

$206K - $356K/yr

... g., RLHF, prompt evaluation). Scale & Operations: Experience scaling large data operations ... Additionally, this role might be eligible for discretionary bonuses or commission payments as well ...

SuperAnnotate AI

Global Account Director

San Francisco, CA · On-site

$350K - $450K/yr

Previous experience selling into AI/ML, data labeling, data annotation, RLHF, or related human-data ... variable commission. Only shortlisted candidates will be contacted for an interview! Equal ...

Toast

Staff Data Scientist

$170K - $272K/yr

Experience fine-tuning LLMs and applying reinforcement learning from human feedback (RLHF) to ... commissions if eligible), equity, and benefits. You can learn more about how we align pay with ...

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Commission Rlhf information

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$50K

$78.6K

$150K

How much do commission rlhf jobs pay per year?

As of Jul 24, 2026, the average yearly pay for commission rlhf in the United States is $78,587.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,500.00 and $78,000.00 per year, depending on experience, location, and employer.

What are Commission RLHF jobs?

Commission RLHF jobs typically involve working on Reinforcement Learning from Human Feedback (RLHF) projects in a commission-based role. RLHF is an approach in artificial intelligence where models are trained using feedback from humans to improve their performance and alignment with human values. People in these jobs might collect and analyze human feedback, design reward models, or fine-tune AI systems. The commission aspect usually means pay is based on deliverables or performance rather than a fixed salary. These roles require strong analytical and communication skills, as well as some familiarity with machine learning concepts.

What are the key skills and qualifications needed to thrive as a Commission RLHF Specialist, and why are they important?

To thrive as a Commission RLHF (Reinforcement Learning from Human Feedback) Specialist, you need a strong background in machine learning, data analysis, and computer science, often supported by an advanced degree in a related field. Familiarity with frameworks like PyTorch or TensorFlow, experience in NLP models, and understanding of annotation tools are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret human feedback and collaborate with cross-functional teams. These skills are essential for developing and refining AI systems that accurately learn from and adapt to human input.

What is the difference between Commission Rlhf vs Real Estate Agent?

AspectCommission RlhfReal Estate Agent
CredentialsReal estate license, RLIHF certificationReal estate license
Work EnvironmentReal estate agencies, brokerage firmsReal estate agencies, brokerage firms
Industry UsageReal estate transactions, property salesProperty sales, leasing, market analysis
Search/Comparison IntentUnderstanding roles, certifications, and dutiesCareer info, licensing, job responsibilities

Commission Rlhf professionals focus on real estate transactions with specific certifications, while real estate agents perform similar duties but may not hold the RLIHF credential. Both work in real estate agencies and assist clients in buying, selling, or leasing properties. The main difference lies in the certification and possibly scope of practice, making it important for clients and job seekers to understand these distinctions.

How do Commission RLHF professionals typically collaborate with cross-functional teams to implement reinforcement learning from human feedback in production environments?

Commission RLHF professionals frequently work alongside data scientists, machine learning engineers, and product managers to integrate reinforcement learning from human feedback (RLHF) into real-world applications. Collaboration often involves aligning on data collection strategies, interpreting human feedback, and iterating on model performance. Effective communication and coordination are crucial, as RLHF requires a blend of technical expertise and an understanding of user intent. Regular team meetings and joint problem-solving sessions help ensure that the RLHF models meet both technical and business objectives.
More about Commission Rlhf jobs
What cities are hiring for Commission Rlhf jobs? Cities with the most Commission Rlhf job openings:
What are the most commonly searched types of Rlhf jobs? The most popular types of Rlhf jobs are:
What states have the most Commission Rlhf jobs? States with the most job openings for Commission Rlhf jobs include:
What job categories do people searching Commission Rlhf jobs look for? The top searched job categories for Commission Rlhf jobs are:
Commission Rlhf jobs near you
Infographic showing various Commission Rlhf job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 10% Part Time, and 9% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution, with an average salary of $78,587 per year, or $37.8 per hour.
Staff Engineer (Agentic AI)

Staff Engineer (Agentic AI)

Kforce Technology Staffing

Phoenix, AZ • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

Job description

RESPONSIBILITIES:
Kforce has a client that is seeking a Staff Engineer (Agentic AI) in Phoenix, AZ.
Duties Include:
* Own the end-to-end development of the enterprise's Agentic AI platform
* Design, develop, test, and deploy high-performance generative AI capabilities that allow AI agents to autonomously understand, plan, and execute multi-step tasks with minimal human oversight
* Ensure the platform is scalable, highly available, and can support mission-critical applications
* Provide technical direction across the organization on GenAI-related projects
* Work closely with Solution and Enterprise Architects to develop solution architectures that integrate LLMs, agent frameworks, and AI services into the broader enterprise system, ensuring alignment with Enterprise Architecture principles and non-functional requirements (security, scalability, resilience, token economics, and latency budgets)
* Lead by example in coding standards, prompt engineering, and context engineering best practices; Conduct code, prompt, and context-pipeline reviews to ensure high code quality, readability, and robust test coverage-including evals, regression suites, and golden datasets for LLM pipelines and API integrations; Establish guidelines for reproducible experiments and version control of prompts, contexts, agents, and datasets (e.g., using Git and LLMOps tools)
* Build internal frameworks and orchestration pipelines to integrate LLMs and agents with enterprise data sources and services; Leverage GenAI tools and protocols (e.g., MCP, A2A, function/tool calling) to enable high-value GenAI business cases across the organization
* Implement LLMOps/GenAI Ops best practices such as automated evaluation, prompt and agent versioning, online/offline evals, observability (traces, token usage, hallucination and grounding metrics), guardrails, and CI/CD pipelines for prompt, agent, and model deployment
REQUIREMENTS:
* 10+ years of experience in designing, developing, and deploying enterprise-scale technology solutions, ideally with two years focused on GenAI/LLM or software architecture initiatives; Demonstrated ability to design and manage complex platforms or products at scale
* 7 - 10 years of progressively complex experience building and scaling enterprise software systems-combined with recent, hands-on application of GenAI or Agentic AI technologies in production environments
* Deep understanding of Generative AI techniques and transformer-based models (e.g., Claude, GPT, or other foundation and open-source LLMs); Hands-on experience integrating, and adapting LLMs into enterprise applications, including expertise in prompt engineering, context engineering, retrieval-augmented generation (RAG), GraphRAG, and agentic patterns (ReAct, planner/executor, multi-agent orchestration) for grounding outputs in enterprise data; Familiarity with multi-agent AI systems and agent-based architectures is highly desirable
* Proficiency in modern GenAI frameworks/libraries such as LangChain, LangGraph, Semantic Kernel, or similar tools; Experience with model-serving runtimes and agent orchestration frameworks for building and managing complex GenAI pipelines; Strong grasp of NLP fundamentals, tokenization, embeddings, and knowledge representation; experience with multimodal models, function calling, structured output, and reinforcement learning from feedback (RLHF/RLAIF) is a plus
* Strong background in data engineering and architecture for AI-ready data-skilled in curating, chunking, enriching, and governing unstructured and semi-structured corpora for LLM consumption; Hands-on experience with vector databases (e.g., pgvector, Elastic Search), hybrid search, reranking, knowledge graphs, and embedding strategies for high-quality retrieval
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.

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