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Junior Nvidia Engineering Jobs in Arizona (NOW HIRING)

Lead AI Engineer

Phoenix, AZ · On-site

$96K - $126K/yr

... junior engineers. • Expert level expertise with NVIDIA's physics-accelerated AI tools such as ... Physics NEMO, Modulus, Warp, or similar platforms for physics-informed deep learning We Value • ...

Junior Nvidia Engineering information

What is a junior Nvidia engineer?

A Junior Nvidia Engineer is an early-career professional who works with Nvidia technologies, such as GPUs, AI hardware, and related software development kits. Their responsibilities typically include assisting in the design, development, testing, and optimization of software or hardware solutions utilizing Nvidia platforms. They often collaborate with senior engineers to solve technical challenges, support product development, and learn about advanced computing technologies. This role is ideal for those interested in graphics processing, machine learning, and high-performance computing. Junior Nvidia Engineers usually have a background in computer science, electrical engineering, or a related field.

What are the key skills and qualifications needed to thrive as a junior Nvidia engineer?

To thrive as a Junior Nvidia Engineer, you need a solid grounding in computer science principles, programming (especially in C++ and Python), and a relevant degree such as Computer Engineering or Electrical Engineering. Familiarity with Nvidia's CUDA platform, GPU architectures, and common development tools like Git and Linux is typically required. Strong problem-solving skills, effective teamwork, and a willingness to learn new technologies are crucial soft skills in this role. These abilities are essential to contribute to innovative hardware and software solutions, collaborate effectively, and adapt to the rapid advancements in GPU technology.

What are some common challenges faced by junior engineers at Nvidia, and how can they overcome them?

As a junior engineer at Nvidia, you may encounter challenges such as adapting to a fast-paced environment, learning proprietary technologies, and collaborating with cross-functional teams. It's common to feel overwhelmed by the complexity of projects and the high expectations for innovation. To overcome these hurdles, proactively seek mentorship from experienced colleagues, participate in internal training sessions, and regularly communicate with your team to clarify goals and expectations. Building strong technical foundations and asking questions when you need support can help you grow quickly in this dynamic environment.

What is the difference between Junior Nvidia Engineering vs Junior Data Scientist?

AspectJunior Nvidia EngineeringJunior Data Scientist
Required CredentialsBachelor's in Computer Science, Electrical Engineering, or related fields; knowledge of CUDA, GPU architectureBachelor's or Master's in Data Science, Statistics, or related fields; programming in Python, R, SQL
Work EnvironmentHardware-focused, engineering labs, GPU development teamsData analysis teams, research environments, software development
Industry UsageTechnology, hardware manufacturing, AI hardware accelerationTech, finance, healthcare, research institutions
Common Search/ComparisonYesYes

Junior Nvidia Engineers focus on GPU hardware, CUDA programming, and hardware development, often working in engineering labs. In contrast, Junior Data Scientists analyze data, develop models, and work with statistical tools. Both roles require strong programming skills but differ in their core focus and industry applications.

What are the most commonly searched types of Nvidia Engineering jobs in Arizona? The most popular types of Nvidia Engineering jobs in Arizona are:
What are popular job titles related to Junior Nvidia Engineering jobs in Arizona? For Junior Nvidia Engineering jobs in Arizona, the most frequently searched job titles are:
What cities in Arizona are hiring for Junior Nvidia Engineering jobs? Cities in Arizona with the most Junior Nvidia Engineering job openings:

$96K - $126K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 24 days ago


Honeywell rating

8.3

Company rating: 8.3 out of 10

Based on 186 frontline employees who took The Breakroom Quiz

67th of 538 rated manufacturers


Job description


As a Lead AI Engineer at Honeywell Aerospace, you will provide expert-level technical leadership in the development of AI-driven engineering design tools and physics-based machine learning models. This role focuses on applying artificial intelligence, physics-informed methods, and surrogate modeling to accelerate the design and analysis of aerospace mechanical systems, including engines, wheels and brakes, environmental control systems, and other complex components. You will help shape the next generation of simulation and analysis capabilities by integrating AI with traditional computational tools such as CFD, FEA, and multi-physics solvers.
In this role, you will craft and lead multi-year research strategies, develop advanced AI surrogates and Physics-AI models, and transition these technologies into engineering workflows across Honeywell Aerospace. You will collaborate with cross-functional teams and global research partners, pursue both internal and government research funding, and guide execution from concept through integration. Your work will significantly impact engineering efficiency, product performance, and Honeywell Aerospace 's leadership in AI-enabled engineering design.
You will report directly to the manager of the AI Research Group and work from our Phoenix, AZ location on a hybrid schedule.
Responsibilities
Key Responsibilities
• Lead development of advanced Physics-AI models and surrogate models to accelerate engineering workflows for CFD, thermal analysis, structural analysis, and system-level simulation.
• Define and drive the AI strategy for engineering design, with a focus on physics-informed neural networks (PINNs), digital twins, and high-fidelity model surrogates.
• Research, develop, and validate new AI methodologies for multi-physics modeling of aerospace components such as engines, wheels and brakes, and mechanical actuation systems.
• Utilize and advance state-of-the-art NVIDIA simulation and AI acceleration tools, including Physics NEMO and related model-based AI frameworks.
• Collaborate closely with engineering teams to integrate surrogate models into design processes, enabling faster trade studies, optimization, and predictive analysis.
• Lead technical execution across internal and government-sponsored R&D projects and contribute to proposal development.
• Mentor AI engineers and researchers, fostering excellence, innovation, and deep technical growth.
Qualifications
US PERSON REQUIREMENT
Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.
You Must Have
• Bachelor's or Master's degree in aerospace engineering, mechanical engineering, or a related engineering discipline.
• Minimum 5 years of experience developing AI models for physics-based simulation, engineering analysis, multi-physics modeling, or surrogate modeling.
• Minimum of 10 years working on design and simulation of physics of engineering systems involving concepts such as Computational Fluid Dynamics or Structural Analysis
• Experience leading technical teams and mentoring junior engineers.
• Expert level expertise with NVIDIA's physics-accelerated AI tools such as Physics NEMO, Modulus, Warp, or similar platforms for physics-informed deep learning
We Value
• Proficiency in Python and machine learning frameworks such as PyTorch and TensorFlow.
• Experience working in structured machine learning deployment environments i.e. MLOps workflows
• Deep knowledge of CFD, structural analysis, thermal modeling, or multi-physics simulation, and the ability to couple these with AI-based surrogates.
• Experience deploying AI models into engineering design workflows or digital engineering ecosystems.
• Strong understanding of current research in physics-informed ML, scientific machine learning, and surrogate modeling at major conferences and journals.
About us:
Join a company that's reintroducing itself to the aviation community we've helped advance for more than a century. At Honeywell Aerospace (NASDAQ: HONA), we're launching as an independent, publicly traded aerospace and defense company built on a legacy of operational excellence and mission-focused execution.
Our new brand identity pairs that heritage with real momentum, as we build technology that helps pilots navigate with confidence, aircraft operate more efficiently, and operators stay ahead of change. With our systems on board 90% of the world's aircraft, your work here has reach that's rare to find anywhere else.
Focusing on our customers, investing in innovation, and building a culture of accountability and performance is how we're shaping what comes next.
Every horizon. Every mission. Every day.
Benefits:
Beyond a performance-driven salary, you'll work alongside dedicated experts on technology that's advancing aviation. As a Honeywell Aerospace employee, you're eligible for a comprehensive benefits package that includes:
  • Employer-subsidized medical, dental, vision and life insurance
  • Short-term and long-term disability coverage
  • 401(k) match, flexible spending accounts and health savings accounts
  • Employee assistance program and educational assistance
  • Parental leave and 12 paid holidays
  • Paid time off for vacation, personal and sick time

Explore your benefits: https://honeywellaerospacebenefits.com/
POSTING TIMELINE
The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates.

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About Honeywell

Sourced by ZipRecruiter

Honeywell is charging into the Industrial IoT revolution with the establishment of Honeywell Connected Enterprise (HCE), building on our heritage of invention and deep, on-the-ground industry expertise. HCE is the leading industrial disruptor, building and connecting software solutions to streamline and centralize the assets, people and processes that help our customers make smarter, more accurate business decisions. Moving at the speed of software, we are creating, innovating and delivering solutions fast, challenging the way things have always been done, piloting new ways for all of us to work, and expecting our successes to set new standards for our customers and for Honeywell. The Chief Architect for Honeywell Connected Enterprise will lead a team of architects and system engineers responsible for the design of applications and infrastructure that deliver high value outcomes for customers in industrial, buildings, distribution centers, and aerospace vertical markets. The Chief Architect will work directly with leadership, development teams, and offering management to design well integrated solutions that utilize software platforming to encourage reuse and speed to market.

Industry

Furniture manufacturing

Company size

10,000+ Employees

Headquarters location

Charlotte, NC, US

Year founded

1906