1

Scientific Machine Learning Jobs in Arizona (NOW HIRING)

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Tempe, AZ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Phoenix, AZ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Mesa, AZ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Tucson, AZ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Gilbert, AZ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a ...

Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal ...

Be Seen First

Requirements · Bachelor's degree in Computer Science, Engineering, Mathematics, or related STEM field · 3+ years of applied machine learning experience with production systems · Demonstrated ...

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong ... Build and optimize machine learning models for classification, regression, predictive analytics ...

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong ... Build and optimize machine learning models for classification, regression, predictive analytics ...

next page

Showing results 1-20

Scientific Machine Learning information

Is ML a high paying job?

Scientific Machine Learning roles typically offer high salaries due to the specialized skills required, such as expertise in deep learning, data analysis, and programming with tools like Python and TensorFlow. Compensation varies by industry, experience, and location but generally exceeds average tech salaries for comparable roles.

Which 3 jobs will survive AI?

Scientific Machine Learning professionals will likely continue to be in demand due to their expertise in developing and applying AI models to complex scientific problems. Roles such as data scientists, AI researchers, and machine learning engineers are expected to persist because they require specialized knowledge, critical thinking, and ongoing innovation that AI tools complement rather than replace. These jobs often involve interdisciplinary skills, programming, and understanding of domain-specific data, making them more resilient to automation.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

How much does a machine learning scientist make?

A machine learning scientist typically earns between $90,000 and $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in deep learning or natural language processing can earn higher salaries, often exceeding $180,000.

What are the key skills and qualifications needed to thrive as a Scientific Machine Learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

Is 40 too late for data science?

Scientific Machine Learning roles often value skills and experience over age, and many professionals transition into data science or machine learning at various stages of their careers. Learning relevant tools like Python, TensorFlow, or scikit-learn and gaining practical experience can help regardless of age, making 40 not too late to pursue this field.
What cities in Arizona are hiring for Scientific Machine Learning jobs? Cities in Arizona with the most Scientific Machine Learning job openings:
Infographic showing various Scientific Machine Learning job openings in Arizona as of June 2026, with employment types broken down into 3% As Needed, 81% Full Time, 13% Part Time, and 3% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.
Senior Machine Learning Scientist

Senior Machine Learning Scientist

Axon

Scottsdale, AZ

$92K - $125K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago


Axon rating

8.6

Company rating: 8.6 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

15th of 139 rated electronics manufacturers


Job description

Your Impact
We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a key member of our research and development efforts, you will play a crucial role in advancing the state-of-the-art in Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Computer Vision and GenAI technologies for law enforcement and beyond. You will collaborate with cross-functional teams to design, develop, and deploy cutting-edge LLM, MLLM, CV models and algorithms and solutions that enable intelligent reasoning, perception and understanding of multimodal data.
What You'll Do
Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company)

  • US: Seattle, Boston, Scottsdale
Responsibilities
  • Own one or more key technical areas across LLM, MLLM, CV product portfolio.
  • Provide technical leadership to junior scientists, guiding the transition of R&D concepts into impactful Axon product feature.
  • Research and develop cutting-edge techniques in LLM, MLLMs, GenAI, and Computer Vision across cloud, devices and sensors based data sources.
  • Design and implement efficient and scalable MLLM models for inference and analysis of multimodal data.
  • Explore novel approaches to address challenges in NLP, NLU, Object Detection, Object Recognition, Object Tracking, Segmentation, and Scene Understanding.
  • Optimize AI models, algorithms for performance, memory footprint, and energy efficiency to meet the requirements of resource-constrained devices.
  • Join force with MLEs or firmware or hardware engineers to leverage hardware accelerators and optimize algorithms for specific hardware architectures.
  • Evaluate the performance of LLM, MLLM, CV models using real-world datasets and design experiments to validate their effectiveness.
  • Stay up-to-date with the latest research trends and advancements in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant findings into our projects.
  • Contribute to patent disclosures, academic publications, and technical documentation to share insights and findings with the broader community.
  • Experience coach and mentor junior scientists.
What You Bring
  • PhD and with +5 years for ML Scientist, +8 years for Sr. ML Scientist, +10 years for Principal ML Scientist experience in Computer Science or a related field with a focus on LLM, MLLMs, Computer Vision, GenAI.
  • Proven track record of research excellence in LLM, MLLM, Computer Vision, Robotics Perception, GenAI, demonstrated through publications in top-tier conferences or journals.
  • Strong proficiency in programming languages such as Python, C/C++, experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras and experience with ROS or robotic operational system.
  • Drive one or more phases of the ML development lifecycle: shape datasets, investigate modeling approaches and architectures, train/evaluate/tune models and implement the end-to-end training pipeline.
  • Leverage state-of-the-art research to deliver high quality models enabling multiple AI projects at scale.
  • Contribute back to the research community via academic publications, tech blogs, open-source code and contributing to internal/external AI challenges
  • Experience in developing computer vision algorithms for resource-constrained devices such as mobile phones, IoT devices, or embedded systems is highly desirable.
  • Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment.
  • Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.
Benefits that Benefit You
  • Competitive salary and 401k with employer match
  • Discretionary paid time off
  • Paid parental leave for all
  • Medical, Dental, Vision plans
  • Fitness Programs
  • Emotional & Mental Wellness support
  • Learning & Development programs
  • And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Location: This role is based out of our Scottsdale, AZ office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesday through Friday, with flexibility to work remotely on Mondays. We believe connection fuels innovation, and our in-office culture is designed to support meaningful teamwork and mentorship.


What Axon employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom