Algorithm Engineer

NextSilicon is reimagining high-performance computing. Our accelerated compute solutions leverage intelligent adaptive algorithms to vastly accelerate supercomputers, driving them forward into a new generation. Our new software-defined hardware architecture enables HPC to fulfill its promise of breakthroughs in all fields of advanced research.

At NextSilicon, everything we do is guided by three core values:

Professionalism: We strive for exceptional results through professionalism and unwavering dedication to quality and performance.
Unity: Collaboration is key to success. That's why we foster a work environment where every employee can feel valued and heard.
Impact: We're passionate about developing technologies that make a meaningful impact on industries, communities, and individuals worldwide.

We are seeking a highly skilled and experienced Research Engineer to join our team. In this role, you will collaborate on developing innovative solutions from concept to implementation and help drive the next major revolution in the computing landscape.

Requirements:

Ph.D. or a strong Master’s degree (or equivalent industry experience) in computer science or a related discipline.
Proven research abilities and a history of innovative work.
Solid software development experience, spanning engineering practices and algorithmic thinking.
Strong Python proficiency and comfort with modern programming languages.
Familiarity with agile development workflows.
Background in graph theory, code analysis, LLVM infrastructure, or SAT solvers is a plus.
Sharp analytical skills and an aptitude for solving complex problems.
Clear and effective written and verbal communication.
Able to thrive both independently and within a collaborative team.

Responsibilities:

Conduct cutting-edge research and experiments in computing and mathematics.
Develop and optimize mathematical algorithms and computations.
Explore new approaches in graph theory, clustering, and related fields to advance a pioneering general-purpose coprocessor architecture.
Analyze data and apply machine learning techniques to improve performance and insights.
Contribute to technical blogs, whitepapers, and scientific publications.
Collaborate with cross-functional teams to translate research into practical solutions.