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Commission Rlhf Jobs (NOW HIRING)

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 ...

... 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 ...

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 ...

Showing results 21-40

Commission Rlhf information

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$50K

$78.6K

$150K

How much do commission rlhf jobs pay per year?

As of Aug 15, 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 is a Commission RLHF?

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?

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.
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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 August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 12% Part Time, and 7% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $78,587 per year, or $37.8 per hour.

AIML - Sr Machine Learning Engineer, Evaluation

Apple Inc.

Cupertino, CA • On-site

$212 - $386.30/hr

Other

Medical, Dental, Retirement

Re-posted 18 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

AIML - Sr Machine Learning Engineer, Evaluation

Cupertino, California, United States Machine Learning and AI

We are seeking a highly skilled and experienced machine learning engineer to join AIML Evaluation to build the systems that evaluate and refine Apple's foundation models and agents. As a key member of the team, you will help design and develop benchmarks, evaluators, simulation environments, and prompt and context optimization pipelines that drive quality improvements across Apple's AI experiences. You will collaborate with product teams and the foundation model team to close the loop between observation and improvement, contributing datasets, environments, and reward signals that drive model and agent quality.

Description

Our team builds the benchmarks, environments, and tooling that power model and agent refinement, and turns observations into actionable opportunities for the next model and agent iteration. We work across the full spectrum of evaluation: offline benchmarks, device-in-the-loop simulation, and on-device observation in production. We develop LLM-as-judge evaluators, train reward models calibrated against human feedback, optimize prompts and context for agents, and contribute targeted datasets and reward signals to foundation model post‑training.

In this role, you will play a crucial role in designing and developing evaluation and refinement infrastructure that supports a broad range of AI products at Apple. You will work on agent and model evaluation across offline, device-in-the-loop, and on-device settings; build automated prompt and context optimization pipelines; and partner with product and research teams to translate failure analysis into measurable model and agent improvements. You will also have the opportunity to engage with product teams across Apple and contribute to advancements in large language models and agentic systems that will reach millions of users.

To succeed in this role, you should have a strong background in machine learning systems, distributed infrastructure, and a proven track record of building and maintaining ML evaluation or training infrastructure. You should be a proactive problem solver with excellent communication skills and the ability to work effectively across multiple codebases, teams, and organizations. Experience with LLM evaluation, reward modeling, prompt optimization, or agentic systems is highly desirable.

Responsibilities
  • Design and build evaluation infrastructure for agents and foundation models.
  • Develop LLM judges, reward models, and prompt optimization pipelines.
  • Build and integrate simulation environments for agent evaluation and trajectory-based data generation.
  • Collaborate with product teams to identify, prioritize, and address quality gaps.
  • Contribute datasets, environments, and reward signals to the foundation model post‑training loop.
Minimum Qualifications
  • Strong background in machine learning and distributed systems.
  • Experience building and maintaining ML infrastructure for evaluation, training, or deployment.
  • Ability to work effectively across multiple codebases, teams, and organizations.
  • 8+ years of professional experience as a software engineer, preferably in machine learning or a related field.
  • Bachelor's or Master's degree in Computer Science or a related field.
Preferred Qualifications
  • Experience with LLM evaluation, LLM-as-judge, or reward modeling.
  • Experience with prompt optimization, agent harness development, or post-training (SFT, DPO, RLHF).
  • Proficiency in Python and ML frameworks such as PyTorch.
  • Experience with agentic systems, simulation environments, or trajectory-based data generation.
  • Familiarity with on-device or privacy-preserving ML.
  • Proactive and determined problem-solving skills.

At Apple, base pay is one part of our total compensation package and is determined within a range. The base pay range for this role is between $212,000 and $386,300, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become shareholders 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 reimbursement for certain educational expenses— including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.

We believe accessibility is a fundamental human right. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Apple accepts applications to this posting on an ongoing basis.

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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