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Deep Learning Developer Jobs in Raleigh, NC (NOW HIRING)

Varsity Tutors

Machine Learning Tutor

Durham, NC · Remote

$18 - $40/hr

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

Varsity Tutors

Machine Learning Tutor

Raleigh, NC · Remote

$18 - $40/hr

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

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Deep Learning Developer information

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$37

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How much do deep learning developer jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for deep learning developer in Raleigh, NC is $37.37, according to ZipRecruiter salary data. Most workers in this role earn between $31.78 and $41.59 per hour, depending on experience, location, and employer.

What is a deep learning developer?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

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

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What are some common challenges deep learning developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.

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

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What cities near Raleigh, NC are hiring for Deep Learning Developer jobs?

Cities near Raleigh, NC with the most Deep Learning Developer job openings:

Deep Learning Developer jobs near you
Infographic showing various Deep Learning Developer job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $77,724 per year, or $37.4 per hour.

Senior Deep Learning Framework Communications Engineer

Durham, NC • On-site

NVIDIA AI
See more jobs at NVIDIA AIexternal

Full-time

Re-posted 22 days ago

Job description

Job Summary:
NVIDIA AI is leading the way in groundbreaking developments in Artificial Intelligence and High Performance Computing. They are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks and improve AI compilers for better performance in multi-GPU environments.
Responsibilities:
• 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.
Qualifications:
Required:
• 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
Preferred:
• 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
Company:
Explore the latest breakthroughs made possible with AI. Founded in , the company is headquartered in Santa Clara, CA, US, , with a team of 10001+ employees. The company is currently Late Stage.

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