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Deep Learning Engineer Jobs in Durham, NC (NOW HIRING)

CoVar

Machine Learning Engineer

Durham, NC · On-site

... TensorFlow • Deep understanding of machine learning fundamentals (gradient descent, cross ... S. or Ph.D in engineering, math, computer science, or related field • Excellent technical ...

CoVar

Machine Learning Engineer

Durham, NC

Deep understanding of machine learning fundamentals (gradient descent, cross-validation, ROC curves ... S. or Ph.D in engineering, math, computer science, or related field * Excellent technical ...

CoVar

Machine Learning Engineer

Durham, NC · On-site

Deep knowledge of state-of-the-art in any of the following: computer vision (preferred), natural ... learning, Bayesian models, etc. • B.S., preferably M.S. or Ph.D in engineering, math, computer ...

Bespoke Labs

Machine Learning Engineer

Raleigh, NC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Durham, NC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

RELX

Machine Learning Engineer Lead

Raleigh, NC

$115K - $192K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML ... This role combines deep ML expertise with distributed systems engineering and AI platform ...

LexisNexis

Machine Learning Engineer Lead

Raleigh, NC · On-site

$115K - $192K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML ... This role combines deep ML expertise with distributed systems engineering and AI platform ...

LexisNexis

Machine Learning Engineer Lead

Raleigh, NC

$115K - $192K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML ... This role combines deep ML expertise with distributed systems engineering and AI platform ...

LexisNexis

Machine Learning Engineer Lead

Raleigh, NC

$115K - $192K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML ... This role combines deep ML expertise with distributed systems engineering and AI platform ...

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Deep Learning Engineer information

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$36.7K

$112K

$185K

How much do deep learning engineer jobs pay per year?

As of Jul 28, 2026, the average yearly pay for deep learning engineer in Durham, NC is $111,961.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,200.00 and $146,400.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior Deep Learning Engineer or AI research director, often involving advanced skills in machine learning frameworks, data modeling, and large-scale system development. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or working in cutting-edge AI research environments.

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 engineers make $500,000?

Senior engineers in high-demand fields such as software, data science, and machine learning can earn $500,000 or more annually, especially with extensive experience, specialized skills, and leadership roles. Roles like senior software engineers, machine learning engineers, and data architects at large tech companies or startups often reach this compensation level through base salary, bonuses, and stock options.

What do deep learning engineers do?

Deep learning engineers develop and implement neural network models to solve complex problems such as image recognition, natural language processing, and speech analysis. They work with large datasets, use frameworks like TensorFlow or PyTorch, and often require knowledge of programming, mathematics, and machine learning principles.

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 engineers make $300,000 a year?

Senior deep learning engineers and AI specialists with extensive experience, advanced skills in machine learning frameworks, and strong domain knowledge can earn $300,000 or more annually. These roles often require advanced degrees, certifications, and work in high-demand industries such as technology, finance, or healthcare, typically involving leadership responsibilities and complex project management.
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Deep Learning Engineer jobs near you
Infographic showing various Deep Learning Engineer job openings in Durham, NC as of July 2026, with employment types broken down into 72% Full Time, 25% Part Time, and 3% Contract. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution, with an average salary of $111,961 per year, or $53.8 per hour.
Senior Deep Learning Framework Communications Engineer

Senior Deep Learning Framework Communications Engineer

Nvidia

Durham, NC • On-site

Full-time

Posted 6 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 245 rated software companies

Job description

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars.

We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect -- for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision?

What you will be doing:

  • Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production

  • Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models.

  • Improve AI compilers to hide communications or perform automatic fusion.

  • Conduct in-depth AI workload performance characterization on multi-GPU clusters.

  • Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads.

  • Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms.

  • Influence the roadmap of communication libraries - NCCL & NVSHMEM.

  • Collaborate with a very dynamic team across multiple time zones.

What we need to see:

  • B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 5+ software engineering and HPC/AI experience

  • Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang

  • Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe)

  • Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile)

  • Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems)

  • Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc)

  • Adaptability and passion to learn new areas and tools

  • Flexibility to work and communicate effectively across different teams and timezones

Ways to stand out from the crowd:

  • Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals)

  • Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes

  • Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout

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 for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 24, 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.

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

Year founded

1993

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