Requirements:

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 programming and 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

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
Addressing complex problems, exercising leadership, and coordinating with multiple teams to achieve objectives

Contributing to industry-leading technology for addressing the toughest problems in operations research
Opportunity to work with forward-thinking and hardworking colleagues
Engage in cutting-edge projects involving AI, robotics, and self-driving cars