Software Engineer, Parallel Scientific Computing at Vorticity Inc

Responsibilities

• Develop high-level reference implementations of scientific applications (e.g. finite-difference time-domain methods, computational fluid dynamics, electromagnetic wave propagation, etc.) from mathematical and algorithmic descriptions.
• Implement and parallelize scientific applications using our proprietary Software Development Kit (SDK) across SPU simulation, emulation, and real-hardware environments.
• Develop and optimize performance critical kernels for the SPU architecture.
• Own iterative performance optimization loops, benchmark, profile, identify bottlenecks, implement improvements and repeat, until we reach our performance targets.
• Understand applications across abstraction layers, from their mathematical formulation to their mapping onto parallel hardware.
• Identify opportunities to improve our compilation flow, runtime, hardware utilization, and overall system efficiency.
• Collaborate with architecture and performance teams to analyze bottlenecks and co-design innovative software and hardware solutions.
• Independently identify problems and opportunities, propose next steps, and drive work forward without requiring detailed task by task direction.
• Write clear, concise technical documentation for Vorticity’s engineers and customers.
• Stay current with parallel programming models, High Performance Computing (HPC) architectures, numerical methods, and techniques for mapping scientific workloads onto parallel hardware.

Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or related field.
• Master's or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or related field.
• 5+ years of experience in modern C++ (CUDA C++ experience strongly preferred) for parallel programming and high-performance computing.
• Exceptional candidates with fewer years but strong skills are also welcome.
• Ability to understand numerical algorithms and translate mathematical descriptions into working implementations.
• Ability and willingness to debug across abstraction layers, from an application or numerical algorithm down through software and into the underlying architecture.
• Strong understanding of computer architecture and the interaction between software and hardware.
• Proficiency with C++, Python, and Linux development environments.
• Excellent written and verbal communication skills.
• Strong ability to work independently and in a team, while taking ownership of ambiguous problems, and determining what needs to be done next.
• Willingness to put in the hard work needed to bring our SPU to life.
• Above all: zero ego.