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Reinforcement Learning Engineer Jobs in Kentucky

$176 - $312/hr

Coordinate distributed teams across design, research, engineering, and operations. * Communicate ... Experience with reinforcement learning from human feedback (RLHF) and preference optimization.

New

$350 - $850/hr

Our team is a quickly growing group of committed researchers, engineers, policy experts, and ... Have experience with reinforcement learning, reward design, or training data curation for LLMs

New

$180 - $290/hr

Model the true cost and margin of customer deals across reinforcement learning, computer use, video ... Work across commercial, engineering, and operations teams to improve financial visibility and ...

$340 - $518/hr

Partner with top research scientists and engineers to identify model failure modes and bridge ... Lead the strategy for high-quality human data collection, including RLHF (Reinforcement Learning ...

$125 - $166/hr

Mentor junior and mid-level engineers through technical review, knowledge sharing, and reinforcement of design standards while fostering a culture of continuous learning and engineering excellence.

New

Showing results 41-47

Reinforcement Learning Engineer information

See Kentucky salary details

$33K

$100.6K

$166.3K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for reinforcement learning engineer in Kentucky is $100,631.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,100.00 and $131,600.00 per year, depending on experience, location, and employer.

What is a reinforcement learning engineer?

Reinforcement Learning Engineers are specialized professionals who design, develop, and implement algorithms based on reinforcement learning, a type of machine learning where agents learn to make decisions by receiving rewards or penalties. They work on building models that enable machines to learn optimal actions through trial and error in complex environments. Their responsibilities often include developing RL architectures, tuning hyperparameters, running simulations, and applying RL methods to real-world problems like robotics, gaming, or recommendation systems. RL Engineers typically have strong backgrounds in computer science, mathematics, and deep learning, along with experience in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are some common challenges faced by reinforcement learning engineers when deploying models in real-world environments?

One of the main challenges Reinforcement Learning (RL) Engineers face is bridging the gap between simulation and real-world deployment. Models that perform well in controlled environments may struggle with unpredictable data, safety constraints, or limited feedback in production. Additionally, RL algorithms often require significant computational resources and careful tuning to avoid instability. Collaboration with domain experts and software engineers is essential to address these issues and ensure successful integration of RL solutions into existing systems.

What are the key skills and qualifications needed to thrive as a reinforcement learning engineer, and why are they important?

To thrive as a Reinforcement Learning Engineer, you need a strong background in machine learning, mathematics (especially probability and statistics), and programming languages like Python, often supported by a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like OpenAI Gym), and cloud computing platforms is typically required. Problem-solving skills, creativity, and effective collaboration help set outstanding engineers apart in this field. These competencies enable the design and deployment of advanced RL solutions that address real-world challenges and drive innovation.

What is the difference between Reinforcement Learning Engineer vs Machine Learning Engineer?

AspectReinforcement Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's in CS, AI, or related; experience with RL frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on RL applicationsTech companies, data-driven firms, AI departments across industries
Industry UsageSpecialized in RL projects like robotics, game AI, autonomous systemsBroader applications including predictive modeling, NLP, computer vision

Reinforcement Learning Engineers focus on developing algorithms that learn through interactions with environments, often in robotics or gaming. Machine Learning Engineers work on a wider range of models and applications. While both roles require strong programming and math skills, RL Engineers specialize in sequential decision-making, whereas ML Engineers handle diverse data-driven tasks across industries.

What are popular job titles related to Reinforcement Learning Engineer jobs in Kentucky?

For Reinforcement Learning Engineer jobs in Kentucky, the most frequently searched job titles are:

What cities in Kentucky are hiring for Reinforcement Learning Engineer jobs?

Cities in Kentucky with the most Reinforcement Learning Engineer job openings:

Infographic showing various Reinforcement Learning Engineer job openings in Kentucky as of August 2026, with employment types broken down into 92% Full Time, and 8% Contract. Highlights an 90% In-person, and 10% Remote job distribution, with an average salary of $100,631 per year, or $48.4 per hour.

Sr Engineering Program Manager, Evaluation - Special Projects

Apple Inc.

On-site

$176 - $312/hr

Other

Medical, Dental, Retirement

Posted 3 days ago

New


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

Cupertino, California, United States Software and Services

Apple's Special Projects team is seeking a Senior Engineering Program Manager (EPM) to lead our AI evaluation framework at the forefront of next-generation AI experiences. This is a highly visible role where you'll drive the strategic direction for how we measure and validate AI model performance across modalities.You will organize and lead teams to architect our evaluation methodology, translating ambiguous product requirements into concrete success metrics that determine if our models meet Apple's quality bar. Your work will directly influence product roadmaps and drive critical hill-climbing decisions that shape the AI experiences millions of users will interact with daily.This role requires mastery of both technical depth in ML evaluation and the ability to influence across teams at the executive level. You'll lead complex, high-stakes programs while mentoring teams and establishing best practices that will define Apple's approach to AI quality.

Description

As the EPM for Evaluation, you will be responsible for :

Responsibilities
  • Strategic Leadership & Vision
  • Partner with technical teams to define and drive the evaluation strategy for Apple's AI models, influencing product roadmaps and technology investments.
  • Partner with stakeholders to align evaluation frameworks with product vision and business objectives.
  • Technical Program Management
  • Develop end-to-end programs to measure and validate performance of state-of-the-art multi-modal models.
  • Drive consensus on subjective quality metrics, establishing clear success criteria for ambiguous use cases.
  • Orchestrate complex data collection initiatives, simulation infrastructure, and evaluation pipelines.
  • Deliver process improvements that increase efficiency across the broader organization.
  • Cross-functional Leadership
  • Coordinate distributed teams across design, research, engineering, and operations.
  • Communicate complex technical concepts and program status directly to executive leadership.
Minimum Qualifications
  • 7+ years of technical program management experience, with at least 3 years leading complex AI/ML programs.
  • Proven track record of delivering complex programs by defining clear requirements and driving engineering teams to successful outcomes.
  • Experience influencing and driving decisions at Director/VP level.
  • Strong ability to navigate ambiguity and lead teams through uncertainty while maintaining program momentum.
  • Excellence in executive communication - ability to distill complex technical information with the right balance of detail.
Preferred Qualifications
  • Master's or PhD in Computer Science, Machine Learning, Statistics, or related quantitative field.
  • Deep hands-on experience with large language models (LLMs), vision-language models (VLMs), and multi-modal architectures.
  • Demonstrated mastery of ML concepts, evaluation methodologies, and the end-to-end model development lifecycle.
  • Experience with reinforcement learning from human feedback (RLHF) and preference optimization.
  • Expertise in statistical analysis, A/B testing, and experimental design at scale.
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 $175,500 and $311,700, 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.

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. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Learn about accessibility in Apple’s workplace
Learn about reasonable accommodations for job applicants

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