... reinforcement learning. * Contribute to the culture of security, compliance, and ethical AI ... Mentor junior engineers and contribute to the growth of Goosehead's AI talent pipeline. Required ...
... reinforcement learning. * Contribute to the culture of security, compliance, and ethical AI ... Mentor junior engineers and contribute to the growth of Goosehead's AI talent pipeline. Required ...
Staff Data Scientist
Beachwood, OH · On-site
... and reinforcement learning where applicable. * Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous ...
Staff Data Scientist
Beachwood, OH · On-site
... and reinforcement learning where applicable. * Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous ...
Staff Data Scientist
Beachwood, OH · On-site +1
... and reinforcement learning where applicable. * Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous ...
Staff Data Scientist
Beachwood, OH · On-site +1
... and reinforcement learning where applicable. * Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous ...
Staff Data Scientist
Beachwood, OH · On-site +1
... and reinforcement learning where applicable. * Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous ...
Staff Data Scientist
Beachwood, OH · On-site +1
... and reinforcement learning where applicable. * Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous ...
Staff Data Scientist
Beachwood, OH · On-site
... reinforcement learning where applicable. Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous improvement.
Staff Data Scientist
Beachwood, OH · On-site
... reinforcement learning where applicable. Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous improvement.
Advanced understanding of LLMs and generative AI, including fine-tuning, RAG pipelines, and prompt engineering. * Familiarity with causal inference, uplift modeling, or reinforcement learning in real ...
Advanced understanding of LLMs and generative AI, including fine-tuning, RAG pipelines, and prompt engineering. * Familiarity with causal inference, uplift modeling, or reinforcement learning in real ...
You have proficiency in programming languages such as Python, R, or SQL. * You have experience with ... You have knowledge of agent-based modeling, reinforcement learning, and autonomous systems is ...
New
You have proficiency in programming languages such as Python, R, or SQL. * You have experience with ... You have knowledge of agent-based modeling, reinforcement learning, and autonomous systems is ...
New
Principal
Hinckley, OH · On-site
The school day is packed full of academic, athletic, and life skills learning. Students focus on ... Develop and/or modify the school's cultural programming and school-wide PBIS process with an ...
Quick apply
Principal
Hinckley, OH · On-site
The school day is packed full of academic, athletic, and life skills learning. Students focus on ... Develop and/or modify the school's cultural programming and school-wide PBIS process with an ...
Delivering consistently high levels of achievement and learning for all students through rigorous ... Develop and/or modify the school's cultural programming and school-wide PBIS process with an ...
Quick apply
Delivering consistently high levels of achievement and learning for all students through rigorous ... Develop and/or modify the school's cultural programming and school-wide PBIS process with an ...
Reinforcement Learning Engineer information
See Cleveland, OH salary details
$36.9K - $50.4K
5% of jobs
$50.4K - $63.9K
7% of jobs
$63.9K - $77.5K
9% of jobs
$80.3K is the 25th percentile. Wages below this are outliers.
$77.5K - $91K
14% of jobs
The median wage is $103.2K / yr.
$91K - $104.5K
16% of jobs
$104.5K - $118.1K
13% of jobs
$118.1K - $131.6K
6% of jobs
$138.8K is the 75th percentile. Wages above this are outliers.
$131.6K - $145.1K
8% of jobs
$145.1K - $158.7K
8% of jobs
$158.7K - $172.2K
7% of jobs
$172.2K - $185.7K
5% of jobs
$36.9K
$112.4K
$185.7K
How much do reinforcement learning engineer jobs pay per year?
As of Aug 24, 2026, the average yearly pay for reinforcement learning engineer in Cleveland, OH is $112,369.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,500.00 and $146,900.00 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?
| Aspect | Reinforcement Learning Engineer | Machine Learning Engineer |
|---|---|---|
| Credentials | Bachelor's/Master's in CS, AI, or related; experience with RL frameworks | Bachelor's/Master's in CS, Data Science, or related; experience with ML algorithms |
| Work Environment | Research labs, AI startups, tech companies focusing on RL applications | Tech companies, data-driven firms, AI departments across industries |
| Industry Usage | Specialized in RL projects like robotics, game AI, autonomous systems | Broader 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 Cleveland, OH?
For Reinforcement Learning Engineer jobs in Cleveland, OH, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Cleveland, OH look for?
The top searched job categories for Reinforcement Learning Engineer jobs in Cleveland, OH are:
What cities near Cleveland, OH are hiring for Reinforcement Learning Engineer jobs?
Cities near Cleveland, OH with the most Reinforcement Learning Engineer job openings:
Full-time
Medical, Dental, Vision, Life, Retirement, PTO
Re-posted 18 days ago
Job description
About Us
AtGooseheadInsurance,we'rechanging the way people think about insurance through a technology-driven, client-first approach. By combining a powerful digital platform with an expert agent network, we empower clients to find the best coverage for their needs-with transparency, efficiency, and trust at the core.
We'rebuilding a data-driven culture that puts analytics at the center of our decision-making. Our team works on high-impact projects across underwriting, marketing, client experience, and agent performance. Ifyou'reexcited to apply machine learning, statistics, and data engineering to solve meaningful business problems,we'dlove to hear from you.
Who You Are:
You are an AI-focused software engineer with a strong foundation in building production systems powered by large language models (LLMs), natural language processing (NLP), and intelligent automation. You thrive at the frontier of research and application, capable of turning cutting-edge models into secure, reliable, and scalable software. You're comfortable in both Fortune 100-style environments and startup-style innovation, and you want to grow your career into senior AI leadership roles.
Key Responsibilities:
Design, build, and deploy agentic AI systems that leverage LLMs, NLP, and retrieval-augmented generation (RAG) pipelines to support both client-facing and agent-facing use cases.
Collaborate with data scientists, product managers, and engineers to translate ambiguous business problems into robust AI-driven solutions.
Develop and maintain scalable APIs and microservices in Python and/or Java that integrate AI capabilities into enterprise applications.
Implement best practices in MLOps, ensuring reproducibility, observability, and seamless deployment of AI models into production.
Drive innovation by staying current with advancements in generative AI, multi-agent frameworks, and reinforcement learning.
Contribute to the culture of security, compliance, and ethical AI adoption across the organization.
Mentor junior engineers and contribute to the growth of Goosehead's AI talent pipeline.
Required Qualifications
3-9 years of professional experience in software engineering or applied AI.
Proficiency in Python and Java, with demonstrated experience building production-grade systems.
Strong background in NLP, LLMs, and generative AI, including prompt engineering, fine-tuning, and orchestration frameworks.
Hands-on experience with MLOps pipelines, containerization (Docker/Kubernetes), and CI/CD.
Experience working with both structured and unstructured datasets.
Strong problem-solving and communication skills, with the ability to explain technical concepts to non-technical stakeholders.
Preferred Qualifications
Exposure to both Fortune 100 enterprises and startup environments, with the ability to balance rigor and speed.
Experience with cloud platforms (Azure, AWS, or GCP) and vector databases.
Familiarity with agentic AI frameworks, autonomous workflows, or multi-agent coordination systems.
Background in insurance, financial services, or other regulated industries.
Experience integrating AI into mission-critical, client-facing applications.
Benefits Summary
High quality voluntary health, vision, disability, life, and dental insurance programs
401K Matching Plan
Employee Stock Purchase Plan
Paid holidays, vacation, and sick leave
Corporate sponsored programs to enhance employee physical, financial, mental,and emotional wellness
Financial Solution Program
Equal Employment Opportunity:
Goosehead is anequal-opportunityemployer andcomplies withall applicable federal, state, and local laws, rules, guidelines, and regulations. Goosehead strictly prohibits and does not tolerate unlawful discrimination against employees, applicants, or any other covered person because of race, color, religion, creed, national origin, ancestry, ethnicity, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender, gender identity, transgender status, age, physical or mental disability, veteran status, uniformed service, genetic information, or any other characteristic protected by applicable law. All applicants for employment and all Goosehead employees are given equal consideration based solely on job-related factors, such as qualifications, experience, performance, and availability.
To learn more about our job opportunities, apply here. We look forward to speaking with you!