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Commission Rlhf Jobs (NOW HIRING)

... RLHF/RLAIF). * Statistical Rigor: Mastery of statistics and experimental design, including ... Outstanding compensation package; competitive commissions for revenue roles and bonuses for non ...

... 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 ...

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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 3, 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:
Infographic showing various Commission Rlhf job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 90% Full Time, and 9% Part Time. Highlights an 62% Physical, 1% Hybrid, and 37% Remote job distribution, with an average salary of $78,587 per year, or $37.8 per hour.
Staff Machine Learning Engineer, Apple Search & Knowledge Platforms

Staff Machine Learning Engineer, Apple Search & Knowledge Platforms

Apple

Santa Clara, CA

$216K - $394K/yr

Full-time

Medical, Dental, Retirement

Posted 16 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 666 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers


Job description

The AI, Search & Knowledge Platforms team builds amazing products and services for Apple's customers while serving as a foundational partner to teams across Apple. The team delivers world-class AI, search, and knowledge systems powering Siri, Apple Intelligence, Safari, and iMessage, and operates the foundational platforms and infrastructure that keep these intelligent experiences running at hyperscale.
As part of this group, you will be doing large scale machine learning and deep learning research and development to improve Open Domain Question Answering (using both structured knowledge graph data and unstructured web data) and Summarization as well as developing fundamental building blocks needed for Artificial Intelligence. This involves developing sophisticated machine learning and large language models (LLMs) to understand user queries, retrieve and rank relevant documents across multiple sources and synthesize information across documents to provide user with a direct answer that best satisfies their intent and information seeking needs. Additionally, you will research and develop the state-of-the-art LLMs for summarizing personal data such as emails, messages, and notifications.
You will also work with researchers and data scientists to develop, fine-tune, and evaluate domain specific Large Language Models for various tasks and applications in Apple’s AI powered products and conduct applied research to transfer the cutting edge research in generative AI to production ready technologies.
Description
In this role, you will work on LLM based question answering and Apple Intelligence features to provide concise, accurate, and grounded information to users to help them complete their tasks quickly on Apple devices.
Your core responsibilities will include:
* Designing and developing advanced Reinforcement Learning technologies in the post-training of generative model, and delivering the end-user experience.
* Driving cross-functional technical initiatives, collaborating with research, engineering and production teams to translate theoretical advances into deployable systems.
* Developing novel and cutting-edge RL algorithms and improving existing ones.
* Staying up to date with the latest RL research and integrate best practices into the team's workflow.
* Working on the end-to-end ML lifecycle: algorithm design and implementation, data collection, model training, evaluation, and deployment.
Preferred Qualifications
Deep expertise in reinforcement learning-based post-training on LLM models, reward modeling, RLHF, RLAIF, Chain-of-thought, and agentic AI R&D.
Deep understanding of cutting edge RL algorithms and large language model.
Deep understanding in LLM pre-training, post-training.
Strong product intuition and ownership
Excellent communication skills
Minimum Qualifications
10+ years of ML experiences in search, natural language processing/understanding. Conversational AI.
Proven experience for LLM post training, including but not limited to SFT, RLHF, RLAIF, Reward Modeling, Chain-of-thought, agentic LLM.
Hands-on experience building RL pipelines and training agents in simulation or real-world environments.
Growth mindset and ability to learn new technologies
MS or Ph.D. in Computer Science, Machine Learning with a specialty in reinforcement learning, or a related field
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $216,200 and $394,000, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976