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Deep Learning Engineer Jobs in Utah (NOW HIRING)

Faculty Lead & Learning Engineer - Sciences

Lehi, UT · On-site

$96K - $126K/yr

Deep disciplinary expertise in one or more core sciences; comfortable stewarding courses across the ... Collaborate with Learning Design, Product, and Engineering to ship high-quality, technology-enabled ...

Evaluate and adopt emerging AI, deep learning, and software engineering technologies that improve product innovation, platform scalability, and engineering productivity. * Partner with Product ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

AI Engineer

Salt Lake City, UT · On-site +1

$101K - $159K/yr

... deep learning models. Ability to build and deploy MCP servers to provide LLMs with secure ... Systems Engineering - Preferred * Automation - Preferred * Test Automation - Preferred * Computer ...

Proven expertise in Machine Learning and Deep Learning, including model design, optimization, and ... Solid grasp of data engineering concepts-including dataset management, feature engineering, and ...

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Showing results 1-20

Deep Learning Engineer information

See Utah salary details

$34.6K

$105.5K

$174.3K

How much do deep learning engineer jobs pay per year?

As of Jun 16, 2026, the average yearly pay for deep learning engineer in Utah is $105,480.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,600.00 and $137,900.00 per year, depending on experience, location, and employer.

What is a Deep Learning Engineer job?

A Deep Learning Engineer is a specialized software engineer who designs, develops, and optimizes deep learning models. They work with neural networks, large datasets, and frameworks like TensorFlow or PyTorch to build AI systems for tasks like image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, performance tuning, and deploying models into production. Strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration are essential for this role.

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

To thrive as a Deep Learning Engineer, you need a strong background in mathematics, machine learning theory, and programming (especially Python), often supported by a relevant degree in computer science, engineering, or related fields. Proficiency with frameworks such as TensorFlow, PyTorch, Keras, as well as experience with GPUs and cloud platforms, is highly valued, and certifications in AI or deep learning can further enhance your profile. Effective problem-solving, strong collaboration skills, and clear communication are important soft skills for excelling in interdisciplinary teams. These abilities ensure that you can develop robust deep learning models, adapt to evolving technologies, and contribute value in both technical and collaborative settings.

What are the typical daily tasks and responsibilities of a Deep Learning Engineer?

Deep Learning Engineers typically spend their days designing, developing, and optimizing neural network models for tasks like image recognition, natural language processing, or recommendation systems. They preprocess and analyze large datasets, experiment with model architectures, and tune hyperparameters to achieve the best performance. Collaboration is often required with data scientists, product managers, and software engineers to integrate models into real-world applications and scale solutions for production. Additionally, many deep learning engineers review current research, stay updated on advancements in AI, and continuously improve their skills. This role offers a dynamic work environment where learning and innovation are highly encouraged.

What are the most commonly searched types of Deep Learning Engineer jobs in Utah? The most popular types of Deep Learning Engineer jobs in Utah are:
What are popular job titles related to Deep Learning Engineer jobs in Utah? For Deep Learning Engineer jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Deep Learning Engineer jobs? Cities in Utah with the most Deep Learning Engineer job openings:
Infographic showing various Deep Learning Engineer job openings in Utah as of June 2026, with employment types broken down into 72% Full Time, 14% Part Time, and 14% Contract. Highlights an 100% In-person job distribution, with an average salary of $105,480 per year, or $50.7 per hour.
Senior Deep Learning Tools Engineer - CUDA Tile

Senior Deep Learning Tools Engineer - CUDA Tile

Nvidia

Salt Lake City, UT

$101K - $138K/yr

Full-time

Posted 9 days ago


Job description

NVIDIA is building advanced compiler technologies to accelerate AI workloads, and we are looking for an engineer focused on performance validation, analysis, and tracking. In this role, you will work at the intersection of deep learning compilers, GPU systems, and automation infrastructure, ensuring that performance improvements are measurable, scalable, and continuously validated over time.

Do you want to help drive the performance of next-generation compilers? Are you excited by how GPU performance powers breakthroughs in deep learning, autonomous systems, and high-performance computing? We are seeking a talented Deep Learning Compiler & Tools Engineer focused on CUDA Tile (Performance & Infrastructure) to join our team.

You will collaborate closely with compiler developers, infrastructure providers, and hardware teams to build systems that track, analyze, and improve performance across rapidly evolving AI workloads. If you're passionate about performance, systems, and building infrastructure that drives real-world impact, we want to hear from you.

What You'll Be Doing:

  • Design and develop performance testing frameworks for deep learning compilers and workloads

  • Build and maintain automated pipelines (CI/CD) to continuously track performance across models, hardware, and compiler changes

  • Implement benchmarking systems to measure latency, throughput, and efficiency of AI and HPC workloads

  • Analyze performance trends over time and identify regressions, bottlenecks, and optimization opportunities

  • Partner with compiler and architecture teams to debug and resolve performance issues

  • Develop tools and dashboards for performance visualization, reporting, and insights

  • Enable scalable testing across diverse GPU systems and environments

  • Improve infrastructure to ensure reliable, reproducible, and high-signal performance data

What We Need to See:

  • BS, MS, or PhD (or equivalent experience) in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or related field

  • 5+ years of software engineering experience, including experience in performance engineering, benchmarking, or systems optimization

  • Strong programming skills in Python (C++ is a plus)

  • Experience with CI/CD systems and automation frameworks

  • Familiarity with hardware-aware performance analysis (GPUs, accelerators, or similar systems)

  • Experience working with deep learning frameworks such as PyTorch, TensorFlow, JAX, or TensorRT

  • Background in data analysis, profiling, and regression tracking

  • Ability to debug complex system-level issues across software and hardware layers

Ways to Stand Out from the Crowd::

  • Experience with GPU performance analysis and optimization

  • Understanding of compiler internals (LLVM, MLIR, CUDA compilation flow)

  • Experience building performance dashboards and large-scale telemetry systems

  • Familiarity with hardware/software co-design or low-level performance tuning

  • Experience with distributed testing infrastructure or large-scale benchmarking systems

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered one of the most desirable employers in the technology industry. Our teams are tackling some of the most challenging problems in AI, deep learning, and accelerated computing.

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 May 10, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.#deeplearning

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993