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

Varsity Tutors

Machine Learning Tutor

Chapel Hill, 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 ...

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 ...

Compunnel

Data Science-II

Raleigh, NC · On-site

... Learning Engineers throughout the model and product production lifecycle. • Apply machine learning algorithms including deep learning, gradient boosting, and random forests. • Work with large ...

Nvidia

Senior Software Engineer, CUTLASS Kernels

Durham, NC · On-site

$118K - $156K/yr

Write Tensor Core-based deep learning kernels such as grouped-GEMM, attention, and convolution ... Strong proficiency in C++ programming and software design, including debugging, performance ...

Nvidia

Senior Software Engineer, CUTLASS Kernels

Durham, NC · On-site

$118K - $156K/yr

Write Tensor Core-based deep learning kernels such as grouped-GEMM, attention, and convolution ... Strong proficiency in C++ programming and software design, including debugging, performance ...

Nvidia

Senior Software Engineer, CUTLASS Platform

Durham, NC · On-site

$118K - $156K/yr

Strong proficiency in C++ programming and software design, including debugging, performance ... Understanding of deep learning models, algorithms, and frameworks. NVIDIA is widely considered to ...

Nvidia

Senior Software Engineer, CUTLASS Platform

Durham, NC · On-site

$118K - $156K/yr

Strong proficiency in C++ programming and software design, including debugging, performance ... Understanding of deep learning models, algorithms, and frameworks. NVIDIA is widely considered to ...

Vulcan Elements

Applied Machine Learning Engineer

Benson, NC · On-site

$93K - $111K/yr

As the Data Engineer, you will design and build the data infrastructure that makes Vulcan ... Deep fluency with data modeling for both operational and analytical workloads; can design schemas ...

Vulcan Elements

Applied Machine Learning Engineer

Durham, NC · On-site

$110K - $132K/yr

As the Data Engineer, you will design and build the data infrastructure that makes Vulcan ... Deep fluency with data modeling for both operational and analytical workloads; can design schemas ...

Compunnel

Data Scientist

Raleigh, NC · On-site

... Learning Engineers throughout the product development and deployment lifecycle. • Design and ... deep learning, gradient boosting, and random forests. • Experience mentoring, training, and ...

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Showing results 41-60

All JobsDeep Learning Engineer JobsDeep Learning Engineer Jobs in Raleigh, NC

Deep Learning Engineer information

See Raleigh, NC salary details

$33.6K

$102.4K

$169.3K

How much do deep learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for deep learning engineer in Raleigh, NC is $102,432.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,400.00 and $133,900.00 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 Raleigh, NC?

For Deep Learning Engineer jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Deep Learning Engineer jobs in Raleigh, NC look for?

The top searched job categories for Deep Learning Engineer jobs in Raleigh, NC are:

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

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

Deep Learning Engineer jobs near you
Infographic showing various Deep Learning Engineer job openings in Raleigh, NC 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 $112,623 per year, or $54.1 per hour.

Senior Machine Learning Engineer III ***Raleigh, NC***

Raleigh, NC • On-site

RELX Group plc
Technology, Communication and Media • 10K+ employees
Learn more about RELX Group plcexternal

$118K - $219K/yr

Full-time

Re-posted 19 days ago

Job description

Are you looking to develop your Machine Learning Engineer career?
Do you enjoy coaching others to achieve high standards?
This is a full-time position based in Raleigh, NC.
(Hybrid - 3 days in office)
About the Role
We are seeking a Consultant-level Machine Learning Engineer to lead the implementation and scaling of AI systems for legal products. This role focuses on how to build and scale-owning system architecture, infrastructure, and productionization of ML/LLM solutions.
You will partner with Data Scientists to turn validated models and prototypes into reliable, high-performance, customer-facing systems.
Key Responsibilities
  • Architect and implement scalable ML/LLM systems in production.
  • Build and deploy LLM applications, including RAG pipelines and agentic systems.
  • Implement hybrid search systems (semantic + lexical) using embeddings and search platforms.
  • Develop and maintain APIs, microservices, and model serving infrastructure.
  • Build data pipelines and streaming systems for large-scale data processing.
  • Define and develop reusable frameworks, libraries, and infrastructure for AI/ML across teams.
  • Optimize systems for latency, scalability, reliability, and cost efficiency.
  • Establish best practices for deployment, monitoring, observability, and CI/CD.
  • Collaborate with Data Scientists to productionize models and integrate into products.
  • Provide technical leadership in system design and engineering standards.

Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • Strong experience implementing and scaling production ML/LLM systems.
  • Deep experience with LLM application development, including RAG and prompt orchestration.
  • Strong experience designing and implementing agentic systems using agent frameworks (e.g., LangChain, LangGraph, AutoGen, Google ADK), including orchestration of multi-step workflows in production environments.
  • Strong experience with hybrid search (semantic + lexical), embeddings, and search platforms (e.g., Solr, OpenSearch).
  • Expertise in distributed systems and cloud-native development, including AWS (S3, DynamoDB).
  • Experience with streaming and messaging systems (e.g., Kafka, SQS) and caching (e.g., Redis).
  • Proficiency in Python and experience with systems languages (e.g., Rust, Go, Scala).
  • Experience building scalable APIs (REST/GraphQL).
  • Experience with containerization and orchestration (Docker, Kubernetes).
  • Strong software engineering fundamentals (system design, testing, CI/CD).

Preferred Qualifications
  • Experience with LLM platforms (e.g., ChatGPT/OpenAI, Claude, Gemini, LangChain, Google ADK).
  • Experience with DevOps and infrastructure as code (e.g., Terraform, CloudFormation, Jenkins).
  • Experience with big data technologies (e.g., Spark, Hadoop).
  • Familiarity with graph databases (e.g., Dgraph, Neo4j, Neptune).
  • Experience building high-availability, low-latency systems.
  • Experience in legal or regulatory domains.

Key Competencies
  • Strong system architecture and scalability mindset.
  • Ownership of implementation, performance, and reliability.
  • Ability to translate data science solutions into production systems.
  • Cross-functional collaboration with DS, product, and platform teams.
  • Excellent debugging, optimization, and operational skills.
  • Clear communication of technical designs and trade-offs.

#AIFluent
U.S. National Base Pay Range: $118,300 - $219,800. Geographic differentials may apply in some locations to better reflect local market rates.This job is eligible for an annual incentive bonus.
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