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Reinforcement Learning Engineer Jobs in Raleigh, NC

AstraZeneca

Agentic AI Scientist

Durham, NC

... reinforcement learning (MARL). Evaluate agent performance in the context of decision making ... Collaborate with cross-functional teams ensuring knowledge transfer to IT engineering teams for ...

AstraZeneca

Agentic AI Scientist

Durham, NC · On-site

... reinforcement learning (MARL). Evaluate agent performance in the context of decision making ... Collaborate with cross-functional teams ensuring knowledge transfer to IT engineering teams for ...

AstraZeneca

Agentic AI Scientist

Durham, NC · On-site

Hands-on experience with reinforcement learning libraries such as OpenAI Gym, Ray RLlib, or Stable ... engineering or chemistry. * Experience with one or more of the following applied machine learning ...

AstraZeneca

Agentic AI Scientist

Durham, NC · On-site

Hands-on experience with reinforcement learning libraries such as OpenAI Gym, Ray RLlib, or Stable ... engineering or chemistry. * Experience with one or more of the following applied machine learning ...

AstraZeneca

Agentic AI Scientist

Durham, NC

Hands-on experience with reinforcement learning libraries such as OpenAI Gym, Ray RLlib, or Stable ... engineering or chemistry. * Experience with one or more of the following applied machine learning ...

CoVar

Signal Processing Engineer

Durham, NC

Signal Processing Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC ... AI/ML algorithm design in the areas of computer vision, reinforcement learning (RL), and natural ...

Wolfspeed, Inc.

Manager of Research Science

Durham, NC · On-site

Use your previous expertise in AI/ML techniques for computer vision, physics informed ML, and reinforcement learning to mentor early-in-career engineers * Bring your previous semiconductor/materials ...

Cree

Manager of Research Science

Durham, NC

Use your previous expertise in AI/ML techniques for computer vision, physics informed ML, and reinforcement learning to mentor early-in-career engineers * Bring your previous semiconductor/materials ...

ReFibuy, Inc.

Full Stack Engineer

Raleigh, NC · On-site

Full Stack Engineer Raleigh, NC | In-office | Full-time Hey Scot here, CEO and co-founder of ... Work on Reinforcement Learning with AI Feedback Loops. Do you stop everything and watch or listen ...

ReFiBuy

Full Stack Engineer

Raleigh, NC · On-site

Full Stack Engineer Raleigh, NC | In-office | Full-time Hey - Scot here, CEO and co-founder of ... Work on Reinforcement Learning with AI Feedback Loops. Do you stop everything and watch or listen ...

ReFibuy, Inc.

Full Stack Engineer

Raleigh, NC

Full Stack Engineer Raleigh, NC | In-office | Full-time Hey - Scot here, CEO and co-founder of ... Work on Reinforcement Learning with AI Feedback Loops. Do you stop everything and watch or listen ...

RELX

Lead Data Scientist

Raleigh, NC

$104.90K - $174.70K/yr

Experience with reinforcement learning, prompt engineering, hallucination mitigation * Working understanding of the business risks associated with applying LLM in a business * Experience working with ...

LexisNexis

Lead Data Scientist

Raleigh, NC · On-site

$104.90K - $174.70K/yr

Experience with reinforcement learning, prompt engineering, hallucination mitigation * Working understanding of the business risks associated with applying LLM in a business * Experience working with ...

LexisNexis

Lead Data Scientist

Raleigh, NC

$104.90K - $174.70K/yr

Experience with reinforcement learning, prompt engineering, hallucination mitigation * Working understanding of the business risks associated with applying LLM in a business * Experience working with ...

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Reinforcement Learning Engineer information

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$36.9K

$112.6K

$186.2K

How much do reinforcement learning engineer jobs pay per year?

As of May 31, 2026, the average yearly pay for reinforcement learning engineer in Raleigh, NC is $112,630.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,700.00 and $147,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Reinforcement Learning Engineer, and why are they important?

To thrive as a Reinforcement Learning Engineer, you need a strong background in machine learning, mathematics (especially probability and statistics), and programming languages like Python, often supported by a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like OpenAI Gym), and cloud computing platforms is typically required. Problem-solving skills, creativity, and effective collaboration help set outstanding engineers apart in this field. These competencies enable the design and deployment of advanced RL solutions that address real-world challenges and drive innovation.

What are some common challenges faced by Reinforcement Learning Engineers when deploying models in real-world environments?

One of the main challenges Reinforcement Learning (RL) Engineers face is bridging the gap between simulation and real-world deployment. Models that perform well in controlled environments may struggle with unpredictable data, safety constraints, or limited feedback in production. Additionally, RL algorithms often require significant computational resources and careful tuning to avoid instability. Collaboration with domain experts and software engineers is essential to address these issues and ensure successful integration of RL solutions into existing systems.

What are Reinforcement Learning Engineers?

Reinforcement Learning Engineers are specialized professionals who design, develop, and implement algorithms based on reinforcement learning, a type of machine learning where agents learn to make decisions by receiving rewards or penalties. They work on building models that enable machines to learn optimal actions through trial and error in complex environments. Their responsibilities often include developing RL architectures, tuning hyperparameters, running simulations, and applying RL methods to real-world problems like robotics, gaming, or recommendation systems. RL Engineers typically have strong backgrounds in computer science, mathematics, and deep learning, along with experience in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What is the difference between Reinforcement Learning Engineer vs Machine Learning Engineer?

AspectReinforcement Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's in CS, AI, or related; experience with RL frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on RL applicationsTech companies, data-driven firms, AI departments across industries
Industry UsageSpecialized in RL projects like robotics, game AI, autonomous systemsBroader applications including predictive modeling, NLP, computer vision

Reinforcement Learning Engineers focus on developing algorithms that learn through interactions with environments, often in robotics or gaming. Machine Learning Engineers work on a wider range of models and applications. While both roles require strong programming and math skills, RL Engineers specialize in sequential decision-making, whereas ML Engineers handle diverse data-driven tasks across industries.

What are popular job titles related to Reinforcement Learning Engineer jobs in Raleigh, NC? For Reinforcement Learning Engineer jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Raleigh, NC look for? The top searched job categories for Reinforcement Learning Engineer jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Reinforcement Learning Engineer jobs? Cities near Raleigh, NC with the most Reinforcement Learning Engineer job openings:
Reinforcement Learning Engineer jobs near you
Senior Deep Learning Framework Communications Engineer

Senior Deep Learning Framework Communications Engineer

Nvidia

Durham, NC

Full-time

Posted 9 days ago

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 June 1, 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.
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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