Job Description Oxford Nanopore Technologies is headquartered at the Oxford Science Park outside Oxford, UK, with satellite offices and a commercial presence in many global locations across the US, APAC and Europe. Oxford Nanopore employs from multiple subject areas including nanopore science, molecular biology and applications, informatics, engineering, electronics, manufacturing and commercialisation. The management team, led by CEO Dr Gordon Sanghera, has a track record of delivering disruptive technologies to the market. Oxford Nanopore’s sequencing platform is the only technology that offers real-time analysis, in fully scalable formats from pocket to population scale, that can analyse native DNA or RNA and sequence any length of fragment to achieve short to ultra-long read lengths. Our goal is to enable the analysis of any living thing, by anyone, anywhere We are seeking a highly skilled and innovative individual to join our team as a GPU Performance Engineer. In this role, you will focus on optimizing machine learning inference for our open-source software, including the base caller dorado, by writing high-performance code for GPUs using CUDA, OpenCL, Metal, and other similar technologies. The majority of our machine learning inference work is deep-learning based. Responsibilities Collaborate with the development team and experienced C++ engineers 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. What We're Looking For 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 Join Us? At Oxford Nanopore Technologies, we are committed to pushing the boundaries of what is possible with single-molecule sensing platforms. By joining our team, you will have the opportunity to work on cutting-edge technology that has the potential to revolutionize fields such as genomics, diagnostics, and more. We offer a dynamic and collaborative work environment where innovation and creativity are encouraged. Please note that no terminology in this advert is intended to discriminate on the grounds of a person's gender, marital status, race, religion, colour, age, disability or sexual orientation. Every candidate will be assessed only in accordance with their merits, qualifications and abilities to perform the duties of the job. About Us Oxford Nanopore’s goal is to bring the widest benefits to society through enabling the analysis of anything, by anyone, anywhere. The company has developed a new generation of nanopore-based sensing technology enabling the real-time, high-performance, accessible and scalable analysis of DNA and RNA. The technology is used in more than 100 countries to understand the biology of humans and diseases, plants, animals, bacteria, viruses and whole environments. Oxford Nanopore was founded in 2005 as a spin-out from the University of Oxford and now employs over 1000 employees around the world.