GPU Performance Optimization Specialist

1 month ago

Oxford, Oxfordshire, United Kingdom Oxford Nanopore Technologies Full time
GPU Performance Engineer

Oxford Nanopore Technologies is a leading innovator in single-molecule sensing platforms, with a mission to revolutionize fields such as genomics, diagnostics, and more. We are seeking a highly skilled and innovative individual to join our team as a GPU Performance Engineer.

Responsibilities:
  • Collaborate with the development team to optimize machine learning inference algorithms for high-performance execution on GPUs.
  • Implement, benchmark, and refine high-performance computing solutions using CUDA, OpenCL, Metal, or other GPU programming frameworks.
  • Analyze and optimize the performance of existing codebases, identifying bottlenecks and implementing solutions to improve efficiency.
  • Focus on optimizing the performance of bioinformatics tools, such as alignment and variant calling.
  • Work closely with software engineers, data scientists, and researchers to integrate performance improvements into our machine learning pipeline.
  • Stay up-to-date with the latest developments in GPU programming and high-performance computing, and apply this knowledge to enhance our software.
  • Document and communicate optimization strategies and results to both technical and non-technical stakeholders.
Requirements:
  • Extensive experience with GPU programming and high-performance computing using CUDA, OpenCL, Metal, or similar technologies.
  • Proven track record of optimizing code for performance and efficiency on GPU architectures.
  • Strong programming skills in C/C++, Python, and other relevant languages.
  • Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or similar is a plus.
  • Ability to work independently and collaboratively within a team environment.
  • Excellent problem-solving skills and attention to detail.
  • Good communication and interpersonal skills with the ability to explain complex technical concepts to a diverse audience.
Preferred Qualifications:
  • A degree in computer science, engineering, mathematics, physics, or a related field, or equivalent experience.
  • Experience with optimizing machine learning inference for bioinformatics or related applications.
  • Knowledge of low-level programming and performance profiling tools.
  • Experience with open-source software development and contribution.
  • Bioinformatics experience is nice to have but not expected.
Why Choose Us?

At Oxford Nanopore Technologies, we offer a dynamic and collaborative work environment where innovation and creativity are encouraged. We are committed to pushing the boundaries of what is possible with single-molecule sensing platforms, and we believe that our team members are the key to achieving this goal.

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