GPU Optimization Specialist

3 months ago

Oxford, Oxfordshire, United Kingdom Oxford Nanopore Technologies Full time

Oxford Nanopore Technologies is a pioneering organization located at the forefront of scientific innovation, with a diverse presence across various global regions.

Our team comprises experts from a wide range of disciplines, including nanopore technology, molecular biology, informatics, engineering, and commercial development. Under the leadership of our CEO, we have a proven history of introducing groundbreaking technologies to the marketplace.

Our unique sequencing platform stands out as the only solution that provides real-time analysis in scalable formats, capable of analyzing native DNA or RNA and sequencing fragments of any length. Our mission is to facilitate the analysis of any biological entity, accessible to anyone, anywhere.

We are in search of a talented and forward-thinking individual to join our team as a GPU Optimization Specialist. In this capacity, you will concentrate on enhancing machine learning inference for our open-source software, particularly the base caller dorado, by developing high-performance code for GPUs utilizing CUDA, OpenCL, Metal, and other related technologies. The majority of our machine learning inference efforts are grounded in deep learning methodologies.

Key Responsibilities:
  • Collaborate with the development team and seasoned C++ engineers to refine machine learning inference algorithms for optimal performance on GPUs.
  • Design, benchmark, and enhance high-performance computing solutions using CUDA, OpenCL, Metal, or other GPU programming frameworks.
  • Evaluate and improve the performance of existing codebases, identifying inefficiencies and implementing effective solutions.
  • Focus on enhancing the performance of bioinformatics tools, including alignment and variant calling.
  • Work closely with software engineers, data scientists, and researchers to incorporate performance enhancements into our machine learning pipeline.
  • Stay informed about the latest advancements in GPU programming and high-performance computing, applying this knowledge to improve our software.
  • Document and convey optimization strategies and outcomes to both technical and non-technical audiences.

Qualifications We Seek:

  • Extensive experience in GPU programming and high-performance computing utilizing CUDA, OpenCL, Metal, or similar technologies.
  • Demonstrated success in optimizing code for performance and efficiency on GPU architectures.
  • Strong programming capabilities in C/C++, Python, and other relevant languages.
  • Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or similar is advantageous.
  • Ability to work both independently and collaboratively within a team setting.
  • Excellent analytical skills and meticulous attention to detail.
  • Strong communication and interpersonal skills, with the ability to articulate complex technical concepts to a varied audience.
Preferred Qualifications:
  • A degree in computer science, engineering, mathematics, physics, or a related field, or equivalent experience.
  • Experience in 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 contributions.
  • Bioinformatics experience is beneficial but not mandatory.

Why Consider Joining Us?

At Oxford Nanopore Technologies, we are dedicated to advancing the possibilities of single-molecule sensing platforms. By becoming part of our team, you will engage with cutting-edge technology that has the potential to transform fields such as genomics and diagnostics. We foster a dynamic and collaborative work environment where innovation and creativity are highly valued.

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