Level

NVIDIAPosted 2d ago

L4

AI Developer Technology Engineer

AI Developer Technology Engineer at NVIDIA scores 90 out of 100 on AI centrality, which makes it a Level 4 role on this board.

Remote (Switzerland, Remote)seniorFull time

AI in this role

Researches and develops techniques to GPU-accelerate deep learning and AI workloads through in-depth analysis and performance optimization.

ccudaopenaccopenmpmpi
computer-visionnlpparallel-programmingdeep-learninggpu-accelerationperformance-optimization

We’re currently seeking a Senior Developer Technology Engineer, Artificial Intelligence.

Would you enjoy researching parallel algorithms to accelerate AI workloads on advanced computer architectures? Do you find it rewarding to identify and eliminate system bottlenecks to achieve the best possible performance on pioneering computer hardware? Could you be thrilled about an opportunity to partner with the developer community, working at the forefront of technology breakthroughs that contribute to the success of an industry leader like NVIDIA? If so, the Developer Technology Team invites you to consider this role.
 

What you will be doing:

  • In this position, you will research and develop techniques to GPU accelerate workloads in deep learning, machine learning or other AI domains.

  • Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex AI and HPC algorithms to ensure optimal AI solutions on modern CPU and GPU architectures.

  • Publish and/or present discovered optimization techniques in developer blogs or relevant conferences to engage and educate the developer community.

  • Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA.

What we need to see:

  • An advanced degree in Computer Science, Computer Engineering, or related computationally focused science degree (or equivalent experience).

  • You have 8+ years of relevant experience in software development or research work.

  • Programming fluency in C/C++ with a deep understanding of algorithms and software development.

  • A background that includes parallel programming, e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, etc.

  • Hands on experience doing low-level performance optimizations.

  • In-depth expertise with CPU and GPU architecture fundamentals.

  • Effective communication and organization skills, with a logical approach to problem solving, good time management, and prioritization skills.

Ways to stand out from the crowd:

  • Expertise in parallelization and performance optimization of Deep Learning models arising from Natural Language Processing, Computer Vision, Recommender Systems, etc.

  • Excellent understanding of linear algebra.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous computer scientist with a genuine passion for parallel computing? If so, we want to hear from you. Come, join our AI Compute DevTech team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field.
 

NVIDIA is committed to fostering a diverse 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.

#deeplearning

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A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Computer VisionNlpParallel ProgrammingDeep LearningGpu AccelerationPerformance OptimizationCCuda

Questions you could be asked

  1. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  2. What NLP problem have you worked on, and how did you measure whether it actually worked?
  3. Tell me about a project where parallel programming 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 gpu acceleration was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Computer Vision, Nlp, Parallel Programming, Deep Learning, and Gpu Acceleration. 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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