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Nvidia Engineering Jobs in Minnesota (NOW HIRING)

Solutions Architect

Virginia, MN · On-site

$60.50 - $79.75/hr

NVIDIA is seeking an extraordinary Financial Services Solutions Architect to join a team of quants and data scientists. You will partner with engineering, product, and sales to design wins and ...

Solutions Architect

Virginia, MN · On-site

$60.50 - $79.75/hr

NVIDIA is seeking an extraordinary Financial Services Solutions Architect to join a team of quants and data scientists. You will partner with engineering, product, and sales to design wins and ...

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Nvidia Engineering information

See Minnesota salary details

$45.5K

$143.8K

$170.4K

How much do nvidia engineering jobs pay per year?

As of Aug 26, 2026, the average yearly pay for nvidia engineering in Minnesota is $143,844.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,100.00 and $169,400.00 per year, depending on experience, location, and employer.

What is an Nvidia engineer?

An Nvidia Engineering job involves designing, developing, and optimizing hardware or software solutions in areas such as graphics processing, AI, and high-performance computing. Engineers at Nvidia work on cutting-edge technologies, including GPUs, deep learning frameworks, and system architecture. Roles vary from hardware design and verification to software development and AI research, depending on expertise. Strong skills in programming, computer architecture, and problem-solving are typically required.

What types of projects do Nvidia engineers typically work on, and how is teamwork structured within the engineering department?

Nvidia Engineers commonly engage in projects related to GPU development, AI and deep learning solutions, software driver optimization, and next-generation hardware innovation. Project teams are often multidisciplinary, bringing together software, hardware, and systems engineers to collaborate closely on end-to-end product development. Engineers frequently work in agile, fast-paced environments, attend regular team stand-ups, and participate in cross-functional meetings. This collaborative structure fosters creativity, accelerates problem-solving, and ensures high-quality product delivery while offering team members exposure to diverse technologies and career growth opportunities.

What are the key skills and qualifications needed to thrive as an Nvidia engineer, and why are they important?

To thrive in Nvidia Engineering, candidates typically need strong proficiency in computer engineering, software development, and a solid understanding of hardware architecture, often backed by a relevant degree such as Electrical Engineering or Computer Science. Familiarity with tools like CUDA, C/C++, Python, and version control systems, as well as experience with GPU programming, are highly valued, and certifications such as Nvidia's Deep Learning Institute credentials can enhance a candidate's profile. Excellent problem-solving, team collaboration, and communication skills set top performers apart in this role. These skills and qualifications enable engineers to contribute effectively to complex, innovative projects that drive Nvidia's technological advancements.

What are the most commonly searched types of Nvidia Engineering jobs in Minnesota?

The most popular types of Nvidia Engineering jobs in Minnesota are:

What job categories do people searching Nvidia Engineering jobs in Minnesota look for?

The top searched job categories for Nvidia Engineering jobs in Minnesota are:

What cities in Minnesota are hiring for Nvidia Engineering jobs?

Cities in Minnesota with the most Nvidia Engineering job openings:

Infographic showing various Nvidia Engineering job openings in Minnesota as of August 2026, with employment types broken down into 90% Full Time, 3% Part Time, 6% Contract, and 1% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $143,844 per year, or $69.2 per hour.

Solutions Architect, Financial Services Banking

Virginia, MN • On-site

$60.50 - $79.75/hr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

The Financial Services Solutions Architect team is looking for an extraordinary person to join an experienced team of Quants and Data Scientists, engaging the finance industry with compelling examples of full-stack accelerated computing. Solutions Architects work with top minds in Financial Services - Banking, Consumer Finance - to accelerate High-Performance Computing and AI workloads across various use cases. We're seeking an inquisitive, hard-working, and creative individual passionate about helping tackle challenges. Join us in this endeavour! What You'll Be Doing: Partner with NVIDIA Engineering, Product, and Sales teams to secure design wins at customers. Enable development and growth of NVIDIA product features through customer feedback and proof-of-concept evaluations. Perform proof-of-concepts working side by side with clients, engineers, and other architects on in-depth analysis, profiling and optimization of machine learning/deep learning models to ensure the best performance on current- and next-generation GPU architectures. Work directly with client ML researchers and developers/engineers on business-impacting workflows, projects, and issues to drive success using NVIDIA technology. Facilitate rapid resolution of customer issues and promote the highest levels of customer satisfaction. Build collateral (notebooks/ blogs) applied to Finance industry use-cases such as ML/DL, recommender systems, GNN, monte-carlo simulations, Quantitative Finance, etc. by working closely with customers. What We Need To See: BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields (or equivalent experience) 5+ years experience as an ML/Software Engineer with a proven track record in writing code in Python, C++ Experience with ML/DL algorithms with frameworks such as TensorFlow, Jax, PyTorch, Spark, Dask Ability to communicate ideas and share code clearly through blog posts, GitHub Enjoy working with multiple levels and teams across organizations (engineering/research, product, sales, and marketing teams) Effective verbal/written communication and technical presentation skills Self-starter with a passion for growth, a real enthusiasm for continuous learning, and sharing findings across the team Ways To Stand Out From The Crowd: Experience building and deploying Banking and Payments modeling techniques, such as: Time-series, Transformers, GraphNNs, XGBoost, Recommender Systems, etc Familiarity with NLP Generative and Agentic AI models, frameworks, and applications Skilled in deploying ML/DL models at scale on on-prem or public cloud computing clusters in production Development experience with NVIDIA software libraries and GPUs Knowledge of MLOps technologies such as Docker/containers, Kubernetes, data center deployments etc. Experience working with enterprise developers building AI, HPC, or data analytics applications NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until August 10, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. #J-18808-Ljbffr