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What you'll be doing:
Designing and implementing groundbreaking techniques in the field of decision science and mathematical optimization.
Performance tuning, optimization, and benchmarking of large-scale parallel numerical software,
Collaborating with other software engineers, internal and external researchers, and a diverse set of internal product teams.
Finding opportunities to improve the code base and reduce code maintenance overhead through re-architecting.
These issues are by nature complex and will require you to find and explain complex solutions, exercise leadership, and coordinate with multiple teams to achieve your objectives.
What we need to see:
PhD or Masters degree in Computer Science, Applied Math, or related science or engineering field of study (or equivalent experience).
Experience developing, debugging, and optimizing high-performance applications with GPU acceleration.
Excellent C++ parallel programmingand software design skills. CUDA is a plus.
Deep understanding of fundamental numerical methods and computations in science and engineering. Experience developing combinatorial or mathematical optimization solvers is a plus.
Strong communication and interpersonal skills are required along with the ability to work in a dynamic team. Experience with mentoring junior engineers and interns is a plus.
5+ years of experience
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