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CUDA Engineer/Developer - LLM Project

Remote: 
Full Remote
Experience: 
Senior (5-10 years)
Work from: 
Luxembourg

Offer summary

Qualifications:

Bachelor’s degree in Computer Science or related field, 5+ years of software development with 2 years in CUDA.

Key responsabilities:

  • Identify and resolve performance issues and bugs on CUDA
  • Analyze and improve algorithm performance through efficient parallelization
  • Stay updated on new CUDA technologies and best practices
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Yo Hr Consultancy SME https://www.yohrconsultancy.com/
11 - 50 Employees
About Yo Hr Consultancy
YO HR (Your Own) human resources established with an ambition to providing Placement to potential Job seekers; headquartered at Indore. Additionally, our competency allows us to negotiate great value, across the country. We recruit across various industry segments. Yo Hr Consultancy is one of the fastest-growing recruitment firms in the country. Yo Hr Consultancy offers a range of recruiting services based on what is best for our clients.
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Job description

CUDA Developer
Experience: 5 - 20 Years
Opportunity: Full Time, Contract, 8 hours (4 Hrs overlap with PST timezone)
Contract length: 6-12-Months

Must-Have:
Total Years Of exp- 5+ years experience mandatory
Mandatory Skills: C++ - 5 years, LLM - 2 years, 2 years exp in CUDA development.

Required Qualifications:
  • Bachelor’s degree in Computer Science, Computer Engineering, or related fields.
  • Minimum of 5 years of software development experience, with at least 2 years specifically in CUDA development.
  • Ability to solve complex problems and work both independently and in a team.
  • Good communication skills and ability to work in a collaborative environment.

Knowledge and Skills:
  • Proficiency in C/C++.
  • Experience with code optimization for performance and efficient resource usage.
  • Experience with CUDA version 12.0 or above (12.3 preferred).
  • Knowledge of frameworks and libraries like cuBLAS and cuDNN.
  • CUDA Performance Optimization.

Job Description:
Position Overview: The ideal candidate should have a strong background in parallel computing and performance optimization using CUDA.
Responsibilities:
  • Identify and resolve performance issues and bugs related to CUDA usage.
  • Analyze and improve algorithm performance through efficient parallelization.
  • Stay updated with new technologies and best practices in CUDA and parallel computing.

Required profile

Experience

Level of experience: Senior (5-10 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Hard Skills

Nvidia CUDALibraryProgram OptimizationC++ (Programming Language)

Other Skills

  • Verbal Communication Skills
  • Collaboration
Are you interested?

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