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Internship Deep Reinforcement Learning Jobs in Ohio

Penske

Staff Data Scientist

Beachwood, OH · On-site

Select and implement appropriate modeling techniques, including classical ML, deep learning, generative AI, and reinforcement learning where applicable. * Oversee the full model lifecycle: data ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

Select and implement appropriate modeling techniques, including classical ML, deep learning, generative AI, and reinforcement learning where applicable. * Oversee the full model lifecycle: data ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

Select and implement appropriate modeling techniques, including classical ML, deep learning, generative AI, and reinforcement learning where applicable. * Oversee the full model lifecycle: data ...

Booz Allen Hamilton, Inc.

AI/ML Engineer, Senior

Dayton, OH · On-site +1

$99K - $225K/yr

You Have: * 5+ years of experience developing ML models such as NLP or LLM, CV, deep learning, generative AI, or reinforcement learning * 5+ years of experience developing AI/ML capabilities to ...

Booz Allen Hamilton

Senior AI/ML Engineer

Dayton, OH · On-site

$99K - $225K/yr

You Have: * 5+ years of experience developing ML models such as NLP or LLM, CV, deep learning, generative AI, or reinforcement learning * 5+ years of experience developing AI / ML capabilities to ...

Phase2 Technology

AI/ML Engineer, Senior

Dayton, OH · On-site

$99 - $225/hr

You Have * 5+ years of experience developing ML models such as NLP or LLM, CV, deep learning, generative AI, or reinforcement learning. * 5+ years of experience developing AI/ML capabilities to ...

New

Booz Allen Hamilton

AI/ML Engineer, Senior

Dayton, OH · Hybrid

$99K - $225K/yr

You Have: * 5+ years of experience developing ML models such as NLP or LLM, CV, deep learning, generative AI, or reinforcement learning * 5+ years of experience developing AI/ML capabilities to ...

City Auto Glass, inc.

Lead Data Scientist

Columbus, OH · On-site

$100 - $130/hr

Drive innovation through the application of cutting‑edge techniques, including deep learning, natural language processing, causal inference, reinforcement learning, and emerging AI technologies.

New

Safelite Group

Lead Data Scientist

Columbus, OH

Deep learning, Natural language processing (NLP), Causal inference, Reinforcement learning and emerging AI technologies. * Serve as the technical escalation point for complex analytical and modeling ...

Goosehead

Data Scientist

Westlake, OH · On-site

Deep experience with SQL and manipulating large-scale datasets across structured and unstructured ... Familiarity with causal inference, uplift modeling, or reinforcement learning in real-world systems.

Pwc

AI & GenAI Data Scientist-Senior Associate

Toledo, OH

$77K - $202K/yr

... reinforcement learning agents - Applying natural language processing techniques for text analytics - Leveraging TensorFlow and Scikit-Learn for deep learning projects Travel Requirements Up to 80 ...

New

Procter & Gamble

Sr. Data Scientist - AI/ML

Cincinnati, OH · On-site

$110K - $165K/yr

Cutting-edge Operations Research (optimization, simulation) * State-of-the-art machine learning (tree models, deep learning, reinforcement learning) * Next-gen Generative AI and Agentic AI techniques ...

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Internship Deep Reinforcement Learning information

What types of projects or tasks can I expect to work on during a deep reinforcement learning internship?

As a Deep Reinforcement Learning (DRL) intern, you'll typically work on projects involving the development, implementation, and evaluation of reinforcement learning algorithms. This might include tasks like training agents in simulated environments, tuning hyperparameters, analyzing performance metrics, and collaborating with team members to integrate DRL solutions into larger systems. You'll also likely spend time reading recent research papers, experimenting with frameworks such as TensorFlow or PyTorch, and presenting your findings to the research team. Collaboration with mentors and other interns is common, and you'll gain hands-on experience that prepares you for more advanced roles in AI research or engineering.

What is an internship in deep reinforcement learning?

An internship in Deep Reinforcement Learning (DRL) is a temporary, hands-on position where interns learn and apply state-of-the-art machine learning algorithms that enable computers to learn decision-making tasks through trial and error. Interns typically work on projects involving neural networks, reward systems, and environments like games or simulations. These internships provide valuable experience with frameworks such as TensorFlow or PyTorch, and exposure to current research in artificial intelligence. The experience helps students or recent graduates build technical skills and prepare for careers in AI research or industry.

What are the key skills and qualifications needed to thrive as an intern in deep reinforcement learning?

To thrive as an Intern in Deep Reinforcement Learning, you need a solid background in mathematics (especially linear algebra, probability, and calculus), programming (Python), and foundational knowledge in machine learning principles, usually supported by ongoing or completed coursework in computer science or related fields. Familiarity with frameworks and tools such as TensorFlow, PyTorch, OpenAI Gym, and experience using version control systems like Git are typically required. Analytical thinking, curiosity, and effective communication are essential soft skills for collaborating on research problems and sharing complex findings. These skills and qualities are crucial for contributing to innovative projects and successfully navigating the challenges of cutting-edge AI research.

What is the difference between Internship Deep Reinforcement Learning vs Data Science Intern?

AspectInternship Deep Reinforcement LearningData Science Intern
Required SkillsMachine learning, programming (Python), reinforcement learning conceptsStatistics, data analysis, programming (Python/R), data visualization
Work EnvironmentResearch labs, AI companies, tech startupsBusiness analytics, tech firms, consulting agencies
Industry UsageAI research, robotics, autonomous systemsBusiness intelligence, marketing, finance

Internship Deep Reinforcement Learning focuses on developing algorithms that enable systems to learn through trial and error, often in AI research or robotics. Data Science Internships involve analyzing data to extract insights and support decision-making. While both roles require programming skills, reinforcement learning emphasizes AI-specific techniques, whereas data science centers on statistical analysis and data visualization.

What are popular job titles related to Internship Deep Reinforcement Learning jobs in Ohio? For Internship Deep Reinforcement Learning jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Internship Deep Reinforcement Learning jobs in Ohio look for? The top searched job categories for Internship Deep Reinforcement Learning jobs in Ohio are:
What cities in Ohio are hiring for Internship Deep Reinforcement Learning jobs? Cities in Ohio with the most Internship Deep Reinforcement Learning job openings:
Internship Deep Reinforcement Learning jobs near you
Infographic showing various Internship Deep Reinforcement Learning job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 67% Full Time, 29% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Staff Data Scientist

Penske

Beachwood, OH • On-site

Full-time

Re-posted 10 days ago

Job description


Staff Data Scientist
Location: Beachwood, OH
Shift: Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate)
Position Summary:
The Staff Data Scientist will be a key role in the Data Science and Analytics team tasked with providing technical leadership for the establishment of enterprise wide capabilities in data science, AI and predictive analytics. The Staff Data Scientist will typically work on 3-5 large projects concurrently that have organization-wide impact. In addition to these projects, the Staff Data Scientist will provide technical consultation, advice and training on all major on-going Data Science and Analytics projects. When required, the Staff Data Scientist will also act as a project manager where vendors, suppliers and consultants are engaged on key strategic and emerging technology initiatives.
Major Responsibilities:
Identifying High Value Analytics & AI Opportunities
  • Partner with business leaders to identify opportunities where predictive analytics, machine learning, or generative AI can improve productivity, reduce cost, or unlock new capabilities.
  • Develop clear business cases and ROI models to prioritize initiatives and communicate value to senior leadership.

Lead Data Science Projects
  • Translate complex business requirements into robust, scalable technical solutions.
  • Select and implement appropriate modeling techniques, including classical ML, deep learning, generative AI, and reinforcement learning where applicable.
  • Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous improvement.
  • Ensure solutions are production ready, maintainable, and aligned with MLOps best practices.
  • Drive organization wide adoption of models and AI systems through clear communication, documentation, and stakeholder engagement.

Technical Guidance & Thought Leadership
  • Provide expert consultation on ML algorithms, model tuning, experimentation frameworks, and cloud native data engineering patterns.
  • Mentor data scientists, ML engineers and AI engineers; support skill development in areas such as forecasting, ML modeling, generative AI, vector databases, and modern ETL/ELT workflows.
  • Contribute to the development of internal standards, reusable components, and best practice guidelines.

Project Management
  • Develop and maintain project plans, milestones, and communication strategies for strategic initiatives.
  • Facilitate regular updates with stakeholders, executives, and cross functional partners.
  • Coordinate with vendors, consultants, and technology partners when external expertise is required

Lead technology change in Data Science, Analytics and AI
  • Evaluate emerging technologies including generative AI platforms, MLOps tools, cloud services, and data engineering frameworks to determine applicability and business value.
  • Recommend and influence adoption of modern, flexible, and scalable technologies that support a unified enterprise data and AI platform.
  • Drive experimentation and prototyping to accelerate innovation and reduce time to value.

Qualifications
Qualifications:
  • Master's Degree required; preferred concentrations in Engineering, Operations Research, Statistics, Applied Math, Computer Science, Data Science or related quantitative field.
  • PhD preferred in Engineering, Operations Research, Statistics, Applied Math, Computer Science, Data Science or related quantitative field.
  • 7+ years of experience along with a PhD in a related field OR 10+ years of experience along with a Master's degree in a related field required.
  • Advanced experience developing and deploying machine learning models using Python and modern ML frameworks (e.g., Scikitlearn, PyTorch, TensorFlow).
  • Strong applied expertise across core ML techniques, including regression, tree based models, clustering, deep learning, and NLP.
  • Familiarity with generative AI and LLMs, including prompt engineering, finetuning, embeddings, and vector databases.
  • Solid understanding of MLOps practices, including CI/CD for ML, automated training pipelines, model versioning, monitoring, and model governance.
  • Hands on experience with cloud based ML platforms (AWS, Azure, or GCP) and containerization/orchestration tools such as Docker and Kubernetes.
  • Working knowledge of modern data ecosystems (Snowflake, Redshift) and the ability to collaborate effectively with data engineering teams when needed.
  • Advanced skill in statistical modeling, SQL, and database concepts required.
  • Demonstrated experience leading small technical teams or pods, providing mentorship and technical direction.
  • Familiarity with Logistics industry is preferred.
  • Regular, predictable, full attendance is an essential function of the job
  • Willingness to travel as necessary, work the required schedule, work at the specific location required, complete Penske employment application, submit to a background investigation (to include past employment, education, and criminal history) and drug screening are required.

Physical Requirements:
-The physical and mental demands described here are representative of those that must be met by an associate to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
-The associate will be required to: read; communicate verbally and/or in written form; remember and analyze certain information; and remember and understand certain instructions or guidelines.
-While performing the duties of this job, the associate may be required to stand, walk, and sit. The associate is frequently required to use hands to touch, handle, and feel, and to reach with hands and arms. The associate must be able to occasionally lift and/or move up to 25lbs/12kg.
-Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception and the ability to adjust focus.
Penske is an Equal Opportunity Employer.
About Us
About Penske Truck Leasing/Transportation Solutions
Penske Truck Leasing/Transportation Solutions is a premier global transportation provider that delivers essential and innovative transportation, logistics and technology services to help companies and people move forward. With headquarters in Reading, PA, Penske and its associates are driven by a dedication to excellence and a commitment to customer success. Visit Go Penske to learn more.

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