JuliaHub · 2 days ago
Symbolic-Numeric Modeling Compiler
Maximize your interview chances
Cloud ComputingSimulation
Insider Connection @JuliaHub
Get 3x more responses when you reach out via email instead of LinkedIn.
Responsibilities
Leverage meta-programming techniques for the construction of domain-specific languages.
Experience with compiler optimization techniques like outlining or loop re-rolling.
Design and implement transpilation and code generation pipelines from custom Static Single Assignment (SSA) intermediate representations to target languages like LLVM and C.
Develop symbolic-numeric passes for a differential-algebraic equations (DAEs) compiler, such as the Pantelides algorithm, system tearing, and alias elimination.
Qualification
Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.
Required
Proven experience with meta-programming, compiler optimization, and domain-specific language construction.
Hands-on experience with system-level modeling languages such as Modelica, Simulink, Simscape, or Amesim.
Strong understanding of transpilation and code generation from custom SSA to LLVM and C.
Familiarity with or willingness to learn symbolic-numeric techniques for DAEs, including the Pantelides algorithm and tearing methods.
Background in numerical differential equations is required
Preferred
Knowledge of numerical methods for DAE integration, including backward differentiation formulae (BDF) methods.
Experience in compiler toolchains, performance engineering, and high-performance computing.
Company
JuliaHub
JuliaHub is a single platform for modeling, simulation, and user built applications.
Funding
Current Stage
Growth StageTotal Funding
$42.82MKey Investors
AEI Horizon XDorilton CapitalNational Science Foundation
2023-06-27Series Unknown· $13M
2021-07-19Series A· $25M
2020-01-21Grant· $0.22M
Recent News
2024-04-14
2024-04-14
2024-04-14
Company data provided by crunchbase