ZipRecruiter

Log In

1

Deep Learning Ai Jobs (NOW HIRING)

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

The position also emphasizes experience with Computer Vision, NLP, Deep Learning, LLMs, Agentic AI, and cloud-based AI infrastructure. Responsibilities * Build and enhance machine learning models ...

Toyon

Deep Learning Algorithm Developer

Goleta, CA · On-site

$120K - $200K/yr

Our researchers apply AI/ML techniques to develop data processing automation solutions for problems ... Requirements Candidates for the Deep Learning Algorithm Developer position should have a strong ...

Toyon

Deep Learning Algorithm Developer

Fort Collins, CO · On-site

$100K - $190K/yr

Our researchers apply AI/ML techniques to develop data processing automation and control solutions ... Requirements Candidates for the Deep Learning Algorithm Developer position should have a strong ...

previous page

Showing results 41-60

All JobsTechnology JobsDeep Learning Ai Jobs

Deep Learning Ai information

See salary details

$11K

$83.9K

$140K

How much do deep learning ai jobs pay per year?

As of Sep 5, 2026, the average yearly pay for deep learning ai in the United States is $83,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What is a deep learning AI professional?

Deep Learning AI professionals are experts who design, develop, and implement artificial intelligence systems that use deep neural networks to analyze complex data and solve tasks such as image recognition, natural language processing, and autonomous decision-making. They work with large datasets and advanced algorithms to build models that can learn and improve over time. These professionals often have a background in computer science, mathematics, or engineering, and are skilled in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive as a deep learning AI engineer?

To thrive as a Deep Learning AI Engineer, you need a strong background in mathematics, programming (especially Python), and experience with neural networks, typically supported by a degree in computer science, engineering, or a related field. Proficiency with deep learning frameworks such as TensorFlow or PyTorch, and knowledge of tools like CUDA for GPU acceleration, are essential; relevant certifications can be advantageous. Analytical thinking, creativity, and effective communication are important soft skills for solving complex problems and collaborating with cross-functional teams. These skills and qualities are crucial for building robust AI models and driving innovation in this rapidly evolving field.

What are some common challenges faced by professionals working in deep learning AI, and how can they be addressed?

Professionals in Deep Learning AI often encounter challenges such as managing large datasets, ensuring model accuracy, and addressing issues like overfitting. Collaboration with data engineers and domain experts is crucial to ensure high-quality data and relevant feature selection. Additionally, staying up-to-date with rapidly evolving frameworks and algorithms requires continuous learning and participation in knowledge-sharing within the team. Regular code reviews and experimentation with different architectures can help overcome technical obstacles and improve model performance.

What is the difference between Deep Learning Ai vs Machine Learning Engineer?

AspectDeep Learning AiMachine Learning Engineer
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of neural networksDegree in Computer Science, Data Science, or related fields; programming skills in Python, R
Work EnvironmentResearch labs, AI development teams, tech companies focusing on AI modelsSoftware development teams, data analysis projects across various industries
Industry UsagePrimarily in AI research, autonomous systems, NLP, computer visionAcross industries for predictive modeling, data analysis, automation

Deep Learning Ai specialists focus on designing and implementing neural network models for complex AI tasks, often requiring advanced knowledge of deep neural networks. Machine Learning Engineers develop broader machine learning models, including traditional algorithms. While both roles require similar educational backgrounds, Deep Learning Ai roles are more specialized in neural networks and AI research, whereas Machine Learning Engineers work across a wider range of algorithms and applications.

More about Deep Learning Ai jobs

What cities are hiring for Deep Learning Ai jobs?

Cities with the most Deep Learning Ai job openings:

What states have the most Deep Learning Ai jobs?

States with the most job openings for Deep Learning Ai jobs include:

What job categories do people searching Deep Learning Ai jobs look for?

The top searched job categories for Deep Learning Ai jobs are:

Deep Learning Ai jobs near you
Infographic showing various Deep Learning Ai job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $83,885 per year, or $40.3 per hour.

Senior Deep Learning Performance Architect

Nvidia

Santa Clara, CA

$196K/yr

Full-time

Re-posted 24 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies

Job description

We are now seeking a Senior Deep Learning Performance Architect. NVIDIA is looking for outstanding Performance Architects with a background in performance analysis, performance modeling, and AI/deep learning to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications. What you'll be doing: Develop innovative architectures to extend the state of the art in deep learning performance and efficiency Analyze performance, cost and power trade-offs by developing analytical models, simulators and test suites Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications Develop, analyze, and harness groundbreaking Deep Learning frameworks, libraries, and compilers Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW What we need to see: MS or PhD in Computer Science, Computer Engineering, Electrical Engineering or equivalent experience 6+ years of meaningful work experience Strong background in GPU or Deep Learning ASIC architecture for training and/or inference Experience with performance modeling, architecture simulation, profiling, and analysis Solid foundation in machine learning and deep learning Strong programming skills in Python, C, C++ Ways to stand out from the crowd: Background with deep neural network training, inference and optimization in leading frameworks (e.g

Pytorch, JAX, TensorRT) Experience with relevant libraries, compilers, and languages - CUDNN, CUBLAS, CUTLASS, MLIR, Triton, CUDA, OpenCL Experience with the architecture of or workload analysis on other DL accelerators Demonstration of self-motivation, with a knack for critical thinking and thinking outside the box Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. NVIDIA's GPUs run AI algorithms, simulating human intelligence, and act as the brains of computers, robots and self-driving cars that can perceive and understand the world.

Increasingly known as "the AI computing company", NVIDIA wants you. Come, join our Deep Learning Architecture team, where you can help build real-time, efficient computing platforms driving our success in this exciting and rapidly growing field. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until January 13, 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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

View All Nvidia Jobs

Apply