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Freelance Computer Vision Deep Learning Engineer Jobs in Utah

Faculty Lead & Learning Engineer - Sciences

Lehi, UT ยท On-site

$96K - $126K/yr

Deep disciplinary expertise in one or more core sciences; comfortable stewarding courses across the ... Competitive salary and equity * Healthcare for you and your dependents (medical, dental, and vision)

CAD Engineer

Magna, UT ยท On-site +1

$60K - $80K/yr

... vision, machine learning, and generative AI within the automotive sector. With over $380M in ... We are seeking an experienced CAD Engineer to join the US Implementation Team. In this role, you ...

Evaluate and adopt emerging AI, deep learning, and software engineering technologies that improve ... Bachelors degree in Computer Science or a closely related technical field. * 8+ years of ...

Machine Learning Engineer

Draper, UT ยท On-site

$121K - $160K/yr

A Machine Learning Engineer helps our learners discover content that is relevant to their interests ... This role is primarily performed in an office or home office setting and involves standard computer ...

... Computer Engineering; or equivalent experience required with an expected graduation date of December 2026 - June 2027 * Good understanding of statistical modeling, machine learning, deep learning, or ...

Senior Machine Learning Engineer

Draper, UT ยท On-site

$145K - $174K/yr

Working here means you become part of a vision-driven team that's ready to tackle challenges and ... As a Senior Machine Learning Engineer , you'll play a pivotal role in designing, building, and ...

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Freelance Computer Vision Deep Learning Engineer information

What engineers make $500,000?

Senior computer vision deep learning engineers with extensive experience, advanced skills in neural networks, and proficiency in frameworks like TensorFlow or PyTorch can earn $500,000 or more annually, especially in high-demand industries such as autonomous vehicles, AI research, or tech giants. Achieving this level often requires a strong educational background, specialized certifications, and a track record of impactful projects.

Is computer vision a dead field?

Computer vision remains a vibrant and evolving field with ongoing research and practical applications, especially in areas like autonomous vehicles, medical imaging, and security. Freelance computer vision deep learning engineers are in demand for developing models using tools like TensorFlow and PyTorch, and staying current with advancements is essential for success.

Is ML full of coding?

Machine learning (ML) roles, including those for a freelance computer vision deep learning engineer, typically involve significant coding, especially in languages like Python and frameworks such as TensorFlow or PyTorch. Strong programming skills are essential for developing, training, and deploying models, although understanding algorithms and data preprocessing are also important components of the job.

Is ML a high paying job?

A career as a machine learning engineer, including roles in computer vision and deep learning, is generally considered high paying due to the specialized skills and demand for expertise in algorithms, programming, and data analysis. Salaries vary based on experience, location, and industry, but these roles often offer competitive compensation compared to other tech positions.
What are the most commonly searched types of Computer Vision Deep Learning Engineer jobs in Utah? The most popular types of Computer Vision Deep Learning Engineer jobs in Utah are:
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What cities in Utah are hiring for Freelance Computer Vision Deep Learning Engineer jobs? Cities in Utah with the most Freelance Computer Vision Deep Learning Engineer job openings:
Senior Deep Learning Tools Engineer - CUDA Tile

Senior Deep Learning Tools Engineer - CUDA Tile

Nvidia

Salt Lake City, UT โ€ข On-site

$101K - $138K/yr

Full-time

Posted 12 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