Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Nature Careers
- ;
- Fraunhofer-Gesellschaft
- Oak Ridge National Laboratory
- California Institute of Technology
- ETH Zurich
- Forschungszentrum Jülich
- University of Dayton
- University of Washington
- AIT Austrian Institute of Technology
- Cold Spring Harbor Laboratory
- Free University of Berlin
- Johns Hopkins University
- King Abdullah University of Science and Technology
- Lawrence Berkeley National Laboratory
- Meta/Facebook
- Nanyang Technological University
- National University of Singapore
- Stanford University
- Technical University of Denmark
- Technical University of Munich
- Texas A&M University
- The Ohio State University
- University of Arkansas
- University of California Davis
- University of California Davis Health System
- University of Glasgow
- University of Maryland, Baltimore County
- University of Minnesota
- University of North Carolina at Greensboro
- University of Pittsburgh
- Washington University in St. Louis
- 22 more »
- « less
-
Field
-
Microscaling Data Formats for Deep Learning INT4 Decoding GQA CUDA Optimizations for LLM Inference Pruning and Distillation to Enable Llama 3.2 1B and 3B Models Suitable for Mobile Devices PyTorch Distributed
-
needs as well as the ability to work in teams Desirable qualifications Knowledge of German Special knowledge in one of these areas is a plus: HPC (e.g., Workload Scheduler, CUDA, Infiniband) Storage (e.g
-
Pytorch, CUDA, Docker, vllm, TGI 6. Familiarity with platforms AWS, GCP, Azure, GitHub, HuggingFace, Spark/Airflow 7. Familiarity with Large Language Models and/or NLP will be advantageous 8
-
LLM training Bright Cluster Manager Pyxis/enroot CUDA System and storage benchmarking DataDirect Networks (DDN) SFA high-performance storage systems Working Conditions This is a hybrid position, in
-
knowledge of programming, software development. Proficiency in at least one programming language such as Python, Fortran, C++, or CUDA, with the ability to learn others as needed. Familiarity with tools
-
Linux kernel internals, computation accelerators (e.g., GPU computing, CUDA), MPI, and OpenMP. Highly resourceful and adept at juggling multiple simultaneous projects. Must demonstrate ability to work
-
, MATLAB, Git, debugging, and modern software engineering practices. Experience with GPU computing (e.g., CUDA, HIP), parallel computing (e.g., MPI, Actor Model). Familiarity with containerization (e.g
-
libraries like NCCL/RCCL and experience with high performance computing middleware is highly desirable. Optimizations of large parallel code bases and experience with GPU programming languages such as CUDA
-
computer science, mathematics or an equivalent with above-average performance You have very good knowledge in one of the following areas: Programming skills in Python, C++ or CUDA Deep learning frameworks
-
optical metrology Experience in the field of software development and/or corresponding programming languages (Python, C++, CUDA and/or MATLAB). Experience in the design of system- or software architectures