ZipRecruiter

Log In

1

Reinforcement Learning Jobs in Arizona (NOW HIRING)

Waabi

Research Scientist, Learnable Planner

Phoenix, AZ · On-site +1

$158K - $269K/yr

Exceptional Bachelor's students will also be considered. - Experience in planning/decision making approaches (e.g., imitation learning, reinforcement learning, optimal control, optimization based ...

Waabi

Research Scientist, Learnable Planner

Phoenix, AZ · On-site +1

$158K - $269K/yr

Exceptional Bachelor's students will also be considered. - Experience in planning/decision making approaches (e.g., imitation learning, reinforcement learning, optimal control, optimization based ...

Waabi

Research Scientist, Simulation Agents

Phoenix, AZ · On-site +1

$158K - $269K/yr

Qualifications: - Masters/PhD in machine learning, computer science, engineering, or a related field. - Strong background in imitation learning and/or reinforcement learning. - Publications in top ...

Waabi

Research Scientist, Simulation Agents

Phoenix, AZ · On-site +1

$158K - $269K/yr

Qualifications: - Masters/PhD in machine learning, computer science, engineering, or a related field. - Strong background in imitation learning and/or reinforcement learning. - Publications in top ...

Intel

Machine Learning Engineer

Phoenix, AZ

Hands-on experience implementing and scaling the full **post-training pipeline** for language models including supervised fine tuning and reinforcement learning. * Previous experiences designing and ...

IntraEdge

Architect

Phoenix, AZ · On-site

$63 - $83/hr

... or reinforcement learning. • Experience in working with large and complex data sets, and using cloud platforms, such as AWS, Azure, or Google Cloud. • Strong analytical, problem-solving ...

next page

Showing results 1-20

All JobsReinforcement Learning JobsReinforcement Learning Jobs in Arizona

Reinforcement Learning information

See Arizona salary details

$26.6K

$54.4K

$74.6K

How much do reinforcement learning jobs pay per year?

As of Jun 23, 2026, the average yearly pay for reinforcement learning in Arizona is $54,372.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,100.00 and $63,400.00 per year, depending on experience, location, and employer.

What are the common responsibilities of a Reinforcement Learning professional on a daily basis?

A typical day for a Reinforcement Learning professional involves designing and implementing learning algorithms, running experiments, analyzing data, and iterating on models to improve performance. You might collaborate closely with data scientists, software engineers, and product managers to integrate your solutions into broader systems or products. Regular activities also include reading recent research literature and participating in team meetings to discuss progress and obstacles. This dynamic role often balances deep technical work with teamwork to drive innovative applications in areas such as robotics, recommendation systems, or autonomous systems.

Who earns more, AI or ML engineer?

Reinforcement Learning engineers, a specialized subset of AI and ML engineers, tend to earn higher salaries due to their advanced skills in developing algorithms for decision-making systems. Overall, AI engineers generally have higher average salaries than ML engineers, but salaries vary based on experience, location, and industry. Both roles require strong programming skills and knowledge of machine learning frameworks.

What are the key skills and qualifications needed to thrive in the Reinforcement Learning position, and why are they important?

To thrive in a Reinforcement Learning role, you need a solid background in mathematics, statistics, machine learning, and programming (commonly with Python), typically supported by a relevant degree such as in computer science or engineering. Experience with frameworks like TensorFlow, PyTorch, OpenAI Gym, and familiarity with large-scale computing systems are highly valued. Strong problem-solving abilities, curiosity, and effective collaboration and communication skills help you excel in multidisciplinary research and project teams. These capabilities are crucial for designing, implementing, and refining complex algorithms that learn from interaction to solve real-world problems.

What engineers make $500,000?

Senior reinforcement learning engineers with extensive experience, advanced skills in machine learning frameworks, and a strong track record in deploying AI systems can earn salaries approaching or exceeding $500,000, especially in high-cost-of-living areas or within leading tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their specialized expertise and impact on product development.

Which 5 jobs will survive AI?

Reinforcement Learning specialists, data scientists, AI researchers, software engineers, and cybersecurity analysts are likely to continue thriving as AI advances, due to their expertise in developing, managing, and securing AI systems. These roles require advanced technical skills, problem-solving abilities, and ongoing learning to adapt to evolving technologies.

What is a Reinforcement Learning job?

A Reinforcement Learning (RL) job involves designing, developing, and optimizing algorithms that enable machines to learn from interactions with their environment. RL professionals work on applications in robotics, finance, gaming, and autonomous systems, leveraging techniques like deep reinforcement learning and policy optimization. Responsibilities often include researching new models, implementing RL algorithms, and improving AI performance. Strong programming skills, knowledge of machine learning frameworks, and an understanding of mathematical concepts like probability and optimization are essential.

Which 3 jobs will survive AI?

Reinforcement Learning specialists, data scientists, and AI ethics professionals are likely to remain in demand as AI advances, due to their specialized skills in developing, managing, and overseeing AI systems. These roles require advanced knowledge of algorithms, programming, and ethical considerations, making them less susceptible to automation. Continuous learning and expertise in AI tools and frameworks help ensure job security in this evolving field.
What are the most commonly searched types of Reinforcement Learning jobs in Arizona? The most popular types of Reinforcement Learning jobs in Arizona are:
What are popular job titles related to Reinforcement Learning jobs in Arizona? For Reinforcement Learning jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning jobs in Arizona look for? The top searched job categories for Reinforcement Learning jobs in Arizona are:
What cities in Arizona are hiring for Reinforcement Learning jobs? Cities in Arizona with the most Reinforcement Learning job openings:
Reinforcement Learning jobs near you

Research Scientist, Learnable Planner

Waabi

Phoenix, AZ • On-site, Remote

$158K - $269K/yr

Full-time

Posted 7 days ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

The Motion Planning team delivers the core module within the autonomy stack that makes decisions and generates trajectories for our self-driving trucks. As a research scientist working on Learnable Planner, you will invent new AI technologies that support scalable planning solutions enabling our launch of fully driverless autonomous trucks. You will contribute towards Waabi's vision of a single AI system that learns end-to-end and in a provably safe manner as well as our revolutionary high-fidelity, closed-loop simulator, Waabi World.
 
You will...
- Design and execute on a research agenda for deep-learning based motion planning for self-driving.
- Leverage and advance the state-of-the-art in robotics and machine learning to enable safe self-driving at scale, with advanced techniques in imitation and reinforcement learning, planning and search, perception and prediction, simulation, foundation models and more.
- Support deploying solutions to our production systems, collaborating closely with platform teams to ensure seamless integration of research findings into production systems.
- Stay up-to-date and advance beyond the state-of-the-art in artificial intelligence, machine learning, computer vision, and self-driving technologies.
- Champion engineering excellence, ensuring high-quality, well structured and tested code.
- Submit and publish work externally at top machine learning, computer vision, and robotics conferences (NeurIPS, ICLR, ICML, CVPR, etc.) and post to our company blog.
 
Qualifications:
- MS/PhD degree in Computer Science, AI, Machine Learning, Computer Vision, Robotics and/or similar technical field(s) of study. Exceptional Bachelor’s students will also be considered.
- Experience in planning/decision making approaches (e.g., imitation learning, reinforcement learning, optimal control, optimization based approaches, search methods, probabilistic decision making).
- Demonstrated research experience through previous internships, work experience, research projects, and papers at top conferences.
- Strong quantitative background and coursework in or working knowledge of linear algebra, calculus, and probability.
- Proficient in reading and coding in Python.
- Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.
 
Bonus/nice to have:
- Previous experience in self-driving technology. 
- Experience deploying ML/DL models to a production motion planning or related robotics stack.
- Proficiency in Pytorch, Rust, C++ and/or CUDA.
The US yearly salary range for this role is: $158,000 - $269,000 USD in addition to competitive perks & benefits. Waabi US Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve! 

Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!

Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.