Deep Learning Solution Architect - RL and Post-training

NVIDIA is hiring a Deep Learning Solution Architect - RL and Post-training in Beijing, China. Level rates it ; you can apply on NVIDIA.

Level's read on this job

Level rates this solutions architect role Builds AI ●●●●: the job is building AI systems.
The posting mentions PyTorch, CUDA and NLP among its tools and skills.
Level classes it as a senior role.
NVIDIA has 2,700+ other open roles on Level.

AI in this role

Drive the development and optimization of reinforcement learning algorithms and infrastructure for LLMs and multimodal models.

PyTorchCUDA

nlpreinforcement-learningllm-trainingdistributed-trainingrlhfprompt-engineering

NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers. You will work closely with industry sales, developer relationship managers and product teams in the hiring position.

What you’ll be doing:

Drive development, and optimization of Reinforcement Learning algorithms and infrastructure for Large Language Models and multimodal models.
Develop and enable prompt open source models support in NVIDIA RL and post-training frameworks.
Collaborate with internal research and engineering teams to adapt and validate state-of-the-art RL methods and optimizations to NVIDIA platform.
Improve Reinforcement Learning initiatives and engagements with customers, providing technical guidance on integrating NVIDIA RL technologies into their AI workflows.
Develop and maintain reusable toolchains, experiment management workflows, and technical documentation to accelerate both internal and customer-facing projects.

What we need to see:

MS or PhD in Computer Science, Artificial Intelligence, Mathematics, or related fields, with solid foundations in algorithms and programming.
5+ years of experience (including research) in Reinforcement Learning, Large Language Model training, or multimodal learning.
Proficient in PyTorch and familiar with RL training frameworks and workflows.
Strong engineering skills with experience in distributed training, task orchestration, or evaluation pipelines.
Ability to work independently with minimal day-to-day direction, and willingness to conduct exploratory experiments on frontier problems.
Desire to be involved in multiple diverse and innovative projects.
Outstanding verbal and written communication skills.

Ways to stand out from the crowd:

Experience with RLHF, GRPO, DPO, or other alignment and post-training methods for LLMs.
Experience with scale-out HPC or cloud architectures for large-scale model training.
CUDA optimization or GPU performance tuning experience.
Experience with agentic AI systems, code generation models, or multimodal RL.
Publications in top-tier venues in RL, NLP, or multimodal learning.

With competitive salaries and a generous benefits package, we are widely considered to be one of the world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you.

How we rate this

Deep Learning Solution Architect - RL and Post-training at NVIDIA rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Deep Learning Solution Architect - RL and Post-training is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in China, Beijing.
The job was posted on August 31, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

NLPReinforcement learningLLM TrainingDistributed TrainingRlhfPrompt engineeringPyTorchCUDA

Also common in solutions architect jobs at this level

Python Generative AI Kubernetes AWS Fine-tuning Machine learning

Pay

Typical solutions architect job: $169k

This posting doesn't list pay. Use the typical solutions architect figure when pay comes up. See solutions architect jobs

Questions you could be asked

What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a project where reinforcement learning was part of your work. What did you do?
Tell me about a project where llm training was part of your work. What did you do?
Tell me about a project where distributed training was part of your work. What did you do?
Tell me about a project where rlhf was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: NLP, Reinforcement learning, LLM Training, Distributed Training, and Rlhf. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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