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NVIDIA

AI Research Scientist

NVIDIA is hiring an AI Research Scientist in Singapore, Singapore. Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • Level rates this research scientist role Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include PyTorch, Python and C.
  • Level classifies it as a senior role.
  • Level lists 2,700+ other open roles at NVIDIA.

AI in this role

Conduct advanced research and develop GPU-accelerated generative AI models, language models, and robotics systems at NVIDIA.

pytorchpythonccuda
computer-visionai-researchmachine-learningdeep-learninggenerative-airoboticsllm

NVIDIA is searching for outstanding AI researchers to join the NVIDIA Research Singapore team. We are dedicated to the development and optimization of GPU-accelerated efficient AI computing, covering language model, visual generation, and robotics. We focuses on pushing the boundaries of generative AI by designing models that are not only powerful but also efficient in terms of computational resources. You will be part of an amazing collaborative research team that consistently publishes at the top venues in machine learning, robotics and computer vision. Your contributions have the chance to create real impact on our products.

What you'll be doing:

  • Research, design and accelerate novel generative AI models on NVIDIA GPUs

  • Publish original research

  • Collaborate with other team members and teams

  • Mentor interns

  • Speak at conferences and events

  • Transfer technology to product groups

  • Collaborate with external researchers outside NVIDIA

What we need to see:

  • Excellent knowledge of LLM and foundation models

  • Publication at leading conferences (ie. CVPR, ICML, ICLR, ICCV, NeurIPS, MLSys, etc)

  • 4 years of experience.

  • PhD degree in computer science or electrical engineering with strong research track records.

  • Excellent programming skills in some rapid prototyping environment such as Python; C++ and parallel programming (e.g., CUDA) is a plus

  • Knowledge of common machine learning frameworks, such as PyTorch

  • Excellent communication skills

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world working for us. Looking forward to hear from you

How we rate this

AI Research Scientist at NVIDIA rates 95 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.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Computer visionAI ResearchMachine learningDeep learningGenerative AIRoboticsLLMPyTorch

Also common in research scientist jobs at this level

Pay

Typical research scientist job
$192k

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

Questions you could be asked

  1. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  2. Tell me about a research question you investigated. What did you find?
  3. Tell me about a project where machine learning was part of your work. What did you do?
  4. Tell me about a project where deep learning was part of your work. What did you do?
  5. Tell me about a project where generative ai was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Computer vision, AI Research, Machine learning, Deep learning, and Generative AI. 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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