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Reinforcement Learning With Human Feedback Jobs in Rochester, NY

East House

Learning & Development Specialist

Rochester, NY · On-site

$24.90 - $42.60/hr

Partners with Human Resources, hiring managers, and program leadership to support a positive ... Evaluates training effectiveness through participant feedback, surveys, assessments, completion ...

Holy Childhood, Inc.

HR Business Partner

Rochester, NY · On-site

$65K - $85K/yr

Assists with recruitment efforts for both Holy Childhood and Special Touch Bakery to include ... Coaches supervisors on feedback delivery, documentation, and corrective action. * Supports annual ...

Amazon

Sr. HR Manager, NACF

Rochester, NY · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

This role requires balancing automation with human insight-leveraging technology, AI, and real-time ... feedback to enhance their capabilities while collaborating on strategies for equitable hiring ...

Paychex

Client HR Business Partner I

Rochester, NY · On-site

  • Medical

  • Retirement

  • PTO

Paychex is reimagining how businesses manage their workforce by bringing payroll, HR, benefits, and ... Our award-winning training and development programs empower our employees with ongoing learning ...

Paychex

Client HR Business Partner I

Rochester, NY

  • Medical

  • Retirement

  • PTO

Our award-winning training and development programs empower our employees with ongoing learning ... Human Resource Strategy - Preferred * Employee Relations Investigations - Preferred * Auditing ...

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Reinforcement Learning With Human Feedback information

See Rochester, NY salary details

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How much do reinforcement learning with human feedback jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for reinforcement learning with human feedback in Rochester, NY is $40.15, according to ZipRecruiter salary data. Most workers in this role earn between $29.18 and $52.16 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a reinforcement learning with human feedback engineer?

To excel as a Reinforcement Learning with Human Feedback (RLHF) Engineer, you need a strong background in machine learning, reinforcement learning theory, statistics, and typically an advanced degree in computer science or a related field. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like Ray RLlib), and experience with data collection and annotation systems are essential. Excellent problem-solving abilities, communication skills, and teamwork help you collaborate with researchers, data annotators, and other engineers. These skills enable you to design and implement RLHF systems that are robust, scalable, and aligned with human values.

What is the difference between Reinforcement Learning With Human Feedback vs Reinforcement Learning Engineer?

AspectReinforcement Learning With Human FeedbackReinforcement Learning Engineer
CredentialsTypically requires knowledge of machine learning, AI, and data analysisRequires similar credentials in machine learning, programming, and AI
Work EnvironmentResearch labs, AI development teams, tech companiesDevelopment teams, research labs, tech firms
Industry UsageUsed in AI training, human-in-the-loop systems, and model refinementDesigning, implementing, and optimizing reinforcement learning algorithms

Reinforcement Learning With Human Feedback focuses on improving AI models through human input, while Reinforcement Learning Engineers develop and deploy these algorithms. Both roles require strong machine learning skills and often work in similar environments, but their core responsibilities differ in application and focus.

What is reinforcement learning with human feedback?

Reinforcement Learning with Human Feedback (RLHF) is a machine learning technique where AI agents are trained not only through automated reward signals but also by incorporating feedback from humans. This approach helps align the agent’s behavior with human preferences, values, or safety requirements by allowing humans to guide or correct the learning process. RLHF is commonly used in developing advanced AI systems, such as language models, to ensure their outputs are helpful, safe, and aligned with user expectations. The process often involves human evaluators ranking or scoring the AI's responses, which are then used to fine-tune the model’s behavior.

What collaborations are typical for a reinforcement learning with human feedback specialist within a machine learning team?

As an RLHF specialist, you often work closely with data scientists, machine learning engineers, and domain experts to design effective feedback mechanisms and reward models. Collaboration with annotation teams or subject matter experts is common, as high-quality human feedback is crucial for training robust RLHF models. You may also partner with product managers and UX researchers to ensure that the models align with user needs and ethical considerations. Regular cross-functional meetings and code reviews help maintain alignment and foster innovation across teams.

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What job categories do people searching Reinforcement Learning With Human Feedback jobs in Rochester, NY look for?

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Reinforcement Learning With Human Feedback jobs near you
Infographic showing various Reinforcement Learning With Human Feedback job openings in Rochester, NY as of August 2026, with employment types broken down into 4% Internship, 67% Full Time, 20% Part Time, and 9% Contract. Highlights an 100% In-person job distribution, with an average salary of $83,520 per year, or $40.2 per hour.

Global Quantitative Strategies | Machine Learning Researcher

Citadel LLC

Rochester, NY • On-site

$300 - $350/hr

Other

Medical, Life, Retirement

Posted 10 days ago

Job description

About GQS

GQS is the quantitative investment business of Citadel. Founded in 2012, GQS has grown rapidly to become one of Citadel’s core investment strategies and one of the top quantitative investment teams in the world. Collaborative teams of researchers, engineers, and traders build robust systems that operate at scale and apply advanced quantitative and machine learning techniques to identify investment opportunities.

Role Overview

Machine Learning Researchers at GQS develop and deploy models across a variety of asset classes. Their work spans deep learning, sequence and time-series modeling, natural language processing, large language models, pre-training, reinforcement learning, and methods for improving robustness in complex financial regimes.

Location

New York, Singapore

Required Skills and Qualifications
  • Advanced degree in Computer Science, Machine Learning, Mathematics, Statistics, Engineering, Physics, or a related quantitative field
  • Proven ability to conduct innovative and impactful research focused on solving real-world problems
  • Deep expertise in machine learning and deep learning, such as sequence modeling, large language models, or reinforcement learning
  • Experience with modern training techniques such as pre-training, fine-tuning, reinforcement learning, or related optimization methods
  • Expertise in Python and machine learning frameworks such as PyTorch or JAX
  • Strong mathematical and statistical foundations
  • Ability to design, implement, and optimize machine learning models for performance, scalability, and robustness
  • Demonstrated interest in financial markets and a drive to apply machine learning techniques to model price formation, market behavior, and risk
Compensation and Benefits

In accordance with applicable law, the base salary range for this role is $300,000 to $350,000. In addition, the employee who fills this role will be eligible to participate in a discretionary incentive compensation program, as well as a wide array of benefit programs, such as medical and life insurance, retirement and tax-free savings plans, and access to other healthcare programs.

Personal Data Use

We collect and use personal data in accordance with our Privacy Policy. We retain data on prospective candidates and may consider suitability for alternative opportunities at Citadel. For more information, see our Privacy Policy.

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