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Machine Learning Robotics Jobs in Arizona (NOW HIRING)

Pwc

CTIO - AI Engineer- Senior Manager

Phoenix, AZ

$91K - $321K/yr

... the implementation of machine learning algorithms and predictive modeling techniques ... Accounting, Analytics/Data Science, Artificial Intelligence/Robotics, Business Administration ...

Pwc

CTIO AI Engineering Manager

Phoenix, AZ

$73K - $244K/yr

... Robotics preferred - Designing, training, and deploying machine learning models - Developing scalable, cloud-native microservices using Docker and Kubernetes - Building end-to-end AI applications ...

MNF Global

EE/CS Patent Agent

Phoenix, AZ · On-site

$150K - $200K/yr

Preferred experience includes patent prosecution in Artificial Intelligence , Machine Learning , 5G-Telecom , Robotics and Semiconductor Manufacturing and Packaging . This opportunity is presented by ...

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All JobsMachine Learning Robotics JobsMachine Learning Robotics Jobs in Arizona

Machine Learning Robotics information

See Arizona salary details

$23.8K

$39.7K

$82K

How much do machine learning robotics jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning robotics in Arizona is $39,683.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,300.00 and $42,900.00 per year, depending on experience, location, and employer.

What is a machine learning robotics?

A Machine Learning Robotics job involves developing algorithms that enable robots to learn from data and improve their performance over time. Professionals in this field work on applications such as autonomous navigation, robotic perception, and human-robot interaction. They use techniques like deep learning, reinforcement learning, and computer vision to enhance a robot's ability to understand and interact with its environment. This role typically requires expertise in machine learning, robotics, and software development, along with strong problem-solving skills.

What are the key skills and qualifications needed to thrive in machine learning robotics?

To excel in Machine Learning Robotics, a strong background in computer science, robotics, and machine learning algorithms, often supported by a relevant degree (such as in engineering or computer science), is essential. Familiarity with programming languages like Python or C++, frameworks such as TensorFlow or ROS (Robot Operating System), and experience with simulation tools are highly valuable, and certifications in AI or robotics can further enhance employability. Strong problem-solving skills, effective communication, and the ability to work collaboratively in cross-disciplinary teams help professionals stand out. These capabilities are crucial for designing, developing, and refining intelligent robotic systems that perform reliably in real-world environments.

What are some common challenges faced by professionals working in machine learning robotics?

Professionals in Machine Learning Robotics often encounter challenges like integrating machine learning models with robotic hardware, ensuring reliable performance in unpredictable real-world settings, and managing computational limitations on embedded systems. Addressing these challenges usually requires creative problem-solving and close collaboration with hardware engineers, software developers, and data scientists. You may also need to continuously refine models and testing processes based on real-time feedback and evolving project goals. This dynamic environment makes the work both demanding and highly rewarding for those eager to push the boundaries of automation and intelligent systems.

What are the most commonly searched types of Machine Learning Robotics jobs in Arizona?

The most popular types of Machine Learning Robotics jobs in Arizona are:

What are popular job titles related to Machine Learning Robotics jobs in Arizona?

For Machine Learning Robotics jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Machine Learning Robotics jobs in Arizona look for?

The top searched job categories for Machine Learning Robotics jobs in Arizona are:

Machine Learning Robotics jobs near you
Infographic showing various Machine Learning Robotics job openings in Arizona as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 72% Full Time, 23% Part Time, 2% Contract, and 1% Nights. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $39,683 per year, or $19.1 per hour.

Research Engineer, Learnable Planner (Integration)

Phoenix, AZ • On-site, Remote

Waabi
See more jobs at Waabiexternal

$159K - $296K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 25 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 engineer for Learnable Planner you will support integration of new AI technologies into our autonomy/planner stack 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...
  • Integrate cutting-edge ML models in production planning stack from development to validation, deployment, and monitoring
  • Develop necessary interfaces and pipelines in simulation for testing prototype or production planning models
  • Work closely with motion planning sub-teams and research scientists to improve our planner architecture and develop rich and novel representations that can facilitate end-to-end solutions
  • Champion engineering excellence, ensuring high-quality, well structured and tested code.
  • Stay up-to-date with the latest advancements in the field of artificial intelligence, machine learning, computer vision, and self-driving technologies, and apply insights from the literature.
  • Work with large datasets from various sources as well as Waabi World, our high-fidelity simulator.
  • Contribute to the publication of research findings in conferences as well as Waabi's blog.
 
Qualifications:
  • MS/PhD in machine learning, computer science, engineering, or a related field. Exceptional Bachelor’s students will also be considered.
  • Experience in ML-based or classical techniques for planning/decision making (e.g., imitation and reinforcement learning, optimization-based approaches, search methods, probabilistic reasoning).
  • Passion for taking research ideas and turning them into practical solutions for real-world applications.
  • Open-minded and collaborative team player with willingness to help others.
  • Solid understanding of computing fundamentals, including code efficiency.
  • Experience in deep learning frameworks such as PyTorch.
  • Proficiency in Python, Rust, C++ and/or CUDA.
 
Bonus/nice to have:
  • Experience deploying ML/DL models to a production motion planning or related robotics stack.
  • Experience in iterating on a model including evaluation, introspection and fine-tuning.
  • Strong grasp of machine learning literature, including current trends and state-of-the-art techniques.
  • Comfortable with model compilation and exporting, lower level concepts like TensorRT, CUDA kernels.
The US yearly salary range for this role is: $159,000 - $296,000 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.