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Reinforcement Learning Engineer Jobs in Wisconsin

Senior AI Engineer

Green Bay, WI · On-site

$101.60K - $139.60K/yr

... reinforcement learning approaches. * Proficiency in multiple programming languages, frameworks, and technologies such as Python, SQL, ReactJS, Node.js, JavaScript, TypeScript, Apache Beam, dbt, and ...

Senior AI Engineer

Green Bay, WI · On-site

$101.60K - $139.60K/yr

... reinforcement learning approaches. * Proficiency in multiple programming languages, frameworks, and technologies such as Python, SQL, ReactJS, Node.js, JavaScript, TypeScript, Apache Beam, dbt, and ...

At least 6+ years of data science/engineering experience * Strong problem-solving skills with an ... Strong practical knowledge of LLM, Reinforcement Learning, Hugging Face, Generative AI, Signal ...

At least 6+ years of data science/engineering experience * Strong problem-solving skills with an ... Strong practical knowledge of LLM, Reinforcement Learning, Hugging Face, Generative AI, Signal ...

Reduce ramp time through experiential learning, coaching, and skillsbased progression, not ... RevOps, Product, Engineering, Marketing * Enablement Strategy, Content Architecture, AI Enablement ...

Be Seen First

At Fundamentals LLC, we believe meaningful change begins with compassionate care, joyful learning ... reinforcement, and following Behavior Support Plans and Behavior Intervention Plans (BIPs ...

New

Be Seen First

At Fundamentals LLC, we believe meaningful change begins with compassionate care, joyful learning ... reinforcement, and following Behavior Support Plans and Behavior Intervention Plans (BIPs ...

New

Promote a culture of continuous learning, engagement, and accountability. * Ensure effective ... Bachelor's degree in Engineering, Business Administration, Food Science, Operations, Supply Chain ...

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Showing results 1-20

Reinforcement Learning Engineer information

See Wisconsin salary details

$38.4K

$116.9K

$193.3K

How much do reinforcement learning engineer jobs pay per year?

As of May 31, 2026, the average yearly pay for reinforcement learning engineer in Wisconsin is $116,948.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,800.00 and $152,900.00 per year, depending on experience, location, and employer.

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 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 Reinforcement Learning Engineers?

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 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 Wisconsin? For Reinforcement Learning Engineer jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Wisconsin look for? The top searched job categories for Reinforcement Learning Engineer jobs in Wisconsin are:
What cities in Wisconsin are hiring for Reinforcement Learning Engineer jobs? Cities in Wisconsin with the most Reinforcement Learning Engineer job openings:
Infographic showing various Reinforcement Learning Engineer job openings in Wisconsin as of May 2026, with employment types broken down into 73% Full Time, and 27% Contract. Highlights an 100% In-person job distribution, with an average salary of $116,948 per year, or $56.2 per hour.
Senior AI Engineer

Senior AI Engineer

Us Venture

Green Bay, WI • On-site

$101.60K - $139.60K/yr

Full-time

Posted 8 days ago


U.S. Venture rating

7.3

Company rating: 7.3 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

166th of 333 rated retail wholesalers


Job description

POSITION SUMMARYJoin our Breakthrough Engineering team with our newly added Senior AI Engineer role! We are seeking a talented and experienced senior level engineer with a background ingenerative AIandmachine learningtojoin our innovative engineering team. In this role, you will contribute to the design, development, and maintenance of full-stack software solutions, with a focus on integrating AI/ML technologies to enhance our products and services.
Over $20 trillion of freight moves through the U.S. economy every year, and most of it is still managed through fragmented data, manual processes, and knowledge that lives in people's heads. We're changing that. Breakthrough is building agentic AI that can reason through complex, customer-specific freight scenarios and operate reliably in workflows where the stakes are measured in real dollars.
Agentic capability is becoming the foundation of how every product in our portfolio works. This is not a side project. You'll join a team of engineers, product managers, and domain experts building production agentic systems from the ground up.
Freight is a deceptively complex domain: fragmented data sources, constantly shifting constraints, and an ecosystem of carriers, shippers, and intermediaries that doesn't sit still.
The problems you'll work on include:
Designing agent reasoning that navigates complex, customer-specific freight scenarios
Solving entity resolution and data integration across diverse data sources
Building evaluation and reliability frameworks that prove agent decisions are sound before they touch customer workflows
Defining orchestration patterns that scale from a single product to platform-wide agentic capability
You'll work with years of real, proprietary freight data. You'll influence how these agents interact with users, working alongside product, design, and domain experts. This is not a research role. We ship. But the people who thrive here think deeply about how agents should work, not just how to make them work right now. If you've been building agentic systems and want to see what happens when they meet a hard, real-world domain with real data and real consequences, this is where that work happens.
This role is open to work on-site in Green Bay or remote/hybrid options based on relevancy of candidate experience.JOB RESPONSIBILITIES

Generative AI and Machine Learning Development:

  • Implement and integrate generative AI models and machine learning algorithms into existing and new software solutions.
  • Fine-tune and optimize pre-trained AI/ML models for specific use cases.
  • Collaborate with engineers and data scientists to build and deploy scalable AI-driven features.

Full Stack Development:

  • Write clean, efficient, and maintainable code for AI-powered software applications.
  • Contribute to both frontend and backend development tasks as part of a cross-functional team, ensuring seamless integration of AI components.

Architectural Design:

  • Work closely with team members and product leads to understand requirements, design AI/ML-enabled features, and contribute to product success.
  • Participate in architectural discussions to determine the best ways to incorporate AI technologies into existing systems.

Technical Excellence:

  • Actively seek opportunities to learn about emerging AI/ML techniques, tools, and platforms.
  • Optimize and refactor code to address performance bottlenecks in AI/ML pipelines.
  • Write and execute robust unit and integration tests for AI/ML models and other software components.
  • Troubleshoot and resolve issues related to AI/ML model performance and system integration.

Innovation:

  • Stay updated on cutting-edge advancements in AI/ML, particularly in generative AI models.
  • Propose and implement creative solutions using AI to solve business problems and enhance user experiences.

Collaboration:

  • Partner with senior, staff, and principal engineers to refine development processes for AI/ML integration.
  • Share knowledge about AI/ML best practices with teammates and mentor junior engineers interested in the field.
QUALIFICATIONS
  • Bachelor's degree in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience

  • 7+ years as a software or data engineer

  • 2+ years experience in AI/ML engineering

  • Experience using AI/ML libraries and frameworks (e.g., Google ADK, LangChain/Graph, Anthropic, GPT, Gemini, Llama, Vertex, TensorFlow, Scikit-learn ) training and fine-tuning machine learning models, including supervised, unsupervised, and reinforcement learning approaches.

  • Proficiency in multiple programming languages, frameworks, and technologies such as Python, SQL, ReactJS, Node.js, JavaScript, TypeScript, Apache Beam, dbt, and BigQuery.

  • Knowledge of application architectures, security best practices, and data integration concepts.

  • Exposure to modern infrastructure such as code technologies like Docker, Kubernetes, Terraform, and Airflow.

  • Understanding of database concepts, data modeling, and data warehousing principles.

  • Understanding of distributed data management systems and related applications.

  • Familiarity with public cloud infrastructure design, tools, and strategies.

  • Knowledge of software development methodologies including Agile, Kanban, and Scrum.

  • Effective communication skills, with the ability to articulate technical concepts to both technical and non-technical stakeholders.

Preferred:

  • Prior experience in a product focused technology team desired.

  • Prior experience with technical problem-solving and the ability to navigate complex technical challenges.





DIVISION:

Breakthrough



U.S. Venture will not offer sponsorship for employment status (including, but not limited to, H-1B, TN, E-3, F1, CPT, OPT, STEM OPT, visa status and other employmentbased nonimmigrant visas) for this position. Accordingly, all applicants must be currently authorized to work in the United States on a fulltime basis and must not require U.S. Venture's sponsorship to continue to work legally in the United States. In general, U.S. Venture does not sponsor candidates for nonimmigrant visas or permanent residency except when there is a specific business need.

U.S. Venture will not accept unsolicited resumes from recruiters or employment agencies. In the absence of an executed recruitment Master Service Agreement, there will be no obligation to any referral compensation or recruiter fee. In the event a recruiter or agency submits a resume or candidate without an agreement, U.S. Venture shall reserve the right to pursue and hire those candidate(s) without any financial obligation to the recruiter or agency. Any unsolicited resumes, including those submitted to hiring managers, shall be deemed the property of U.S. Venture.

U.S. Venture, Inc. is an equal opportunity employer that is committed to inclusion and diversity. We ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender, gender identity or expression, marital status, age, national origin, disability, veteran status, genetic information, or other protected characteristic. If you need assistance or an accommodation due to a disability, you may call Human Resources at (920) 739-6101.



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