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Deep Learning Engineer Jobs in Denver, CO (NOW HIRING)

Cymertek

Machine Learning Engineer

Aurora, CO · On-site

SIMILAR CAREER TITLES Data Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML ...

Cymertek

AI/ML Engineer

Aurora, CO · On-site

SIMILAR CAREER TITLES Machine Learning Engineer, Artificial Intelligence Engineer, Data Scientist, Deep Learning Engineer, NLP Engineer, Computer Vision Engineer, AI Research Scientist, Robotics ...

Cymertek Corporation

AI/ML Engineer

Aurora, CO · On-site

$125 - $150/hr

SIMILAR CAREER TITLES Machine Learning Engineer, Artificial Intelligence Engineer, Data Scientist, Deep Learning Engineer, NLP Engineer, Computer Vision Engineer, AI Research Scientist, Robotics ...

Ibotta, Inc

Principal Machine Learning Engineer

Denver, CO · On-site

$228K - $253K/yr

Ibotta is seeking a Principal Machine Learning Engineer to join our Core Data & Analytics team and ... Deep hands-on experience prototyping, building, releasing, and monitoring mission-critical machine ...

Owl AI

Machine Learning Engineer

Boulder, CO · On-site

$150 - $200/hr

Five to ten years of engineering experience, spanning applied machine learning and the ... Deep proficiency in Python for model development, data processing, and production ML code. * Hands ...

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Deep Learning Engineer information

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$38.6K

$117.6K

$194.3K

How much do deep learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for deep learning engineer in Denver, CO is $117,580.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,200.00 and $153,700.00 per year, depending on experience, location, and employer.

What is a deep learning engineer?

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 does a deep learning engineer do?

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 skills and qualifications does a deep learning engineer need?

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.

Are deep learning engineers in demand?

Deep learning engineers are in high demand due to the growth of artificial intelligence and machine learning applications across industries such as technology, healthcare, and finance. They typically require skills in neural networks, programming languages like Python, and frameworks such as TensorFlow or PyTorch, with job opportunities increasing as AI adoption expands.

What are popular job titles related to Deep Learning Engineer jobs in Denver, CO?

For Deep Learning Engineer jobs in Denver, CO, the most frequently searched job titles are:

What job categories do people searching Deep Learning Engineer jobs in Denver, CO look for?

The top searched job categories for Deep Learning Engineer jobs in Denver, CO are:

Deep Learning Engineer jobs near you
Infographic showing various Deep Learning Engineer job openings in Denver, CO as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $119,257 per year, or $57.3 per hour.

Senior Deep Learning Engineer - Autonomous Vehicles

Boulder, CO • On-site

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidiaexternal

$108K - $148K/yr

Full-time

Posted 23 hours ago

Posted today

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

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. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are in search of a Senior Deep Learning Systems Engineer to propel NVIDIA's Autonomous Vehicles project forward. In this role, you will build and scale training libraries and infrastructure that make end-to-end autonomous driving models possible. By enabling training on thousands of GPUs and massive datasets, you will accelerate iteration speed and improve safety, working closely with research and platform teams across NVIDIA.

What you'll be doing:

  • Crafting, scaling, and hardening deep learning infrastructure libraries and frameworks for training on multi-thousand GPU clusters.

  • Improving efficiency throughout the training stack: data loaders, distributed training, scheduling, and performance monitoring.

  • Building robust training pipelines and libraries to handle massive video datasets and enable rapid experimentation.

  • Collaborating with researchers, model engineers, and internal platform teams to enhance efficiency, minimize stalls, and improve training availability.

  • Owning core infrastructure components such as orchestration libraries, distributed training frameworks, and fault-resilient training systems.

  • Partnering with leadership to ensure infrastructure scales with growing GPU capacity and dataset size while maintaining developer efficiency and stability.

What we need to see:

  • BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or a related field, or equivalent experience.

  • 12+ years of professional experience building and scaling high-performance distributed systems, ideally in ML, HPC, or large-scale data infrastructure.

  • Extensive knowledge in deep learning frameworks (PyTorch is preferred), large scale training (DDP/FSDP, NCCL, tensor/pipeline parallelism), and performance profiling.

  • Strong systems background: datacenter networking (RoCE, IB), parallel filesystems (Lustre), storage systems, schedulers (Slurm, Kubernetes, etc.).

  • Proficiency in Python and C++, with experience writing production-grade libraries, orchestration layers, and automation tools.

  • Ability to work closely with multi-functional teams (ML researchers, infra engineers, product leads) and translate requirements into robust systems.

Ways to stand out from the crowd:

  • Shown experience scaling large GPU training clusters with >1,000 GPUs.

  • Contributions to open-source ML systems libraries (e.g., PyTorch, NCCL, FSDP, schedulers, storage clients).

  • Expertise in fault resilience and high availability, including elastic training and large-scale observability.

  • Tried leadership skills as a hands-on technical authority, encouraging others and establishing guidelines for ML systems engineering.

  • Familiarity with reinforcement learning (RL) at scale, particularly in the context of simulation-heavy workloads.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 12, 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.#deeplearning

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

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