Simulation Engineer

Astrome; Bengaluru; Presencial; INR 1.200.000 - 1.800.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health Insurance

ESOPs

Gratuity

PF

Descripción de la vacante

Astrome Technologies Pvt. Ltd. in Bengaluru seeks engineers to develop a high-performance simulation engine in C++. You will implement adaptive-step numerical integration, quaternion-based dynamics, and robust coordinate frame transforms for physics simulations.

Responsibilities include optimizing shared memory usage, exploring intra-job parallelism with OpenMP or MPI, and building Kalman-filter based state estimation. Strong memory management and CMake/testing experience are required.

Formación

• Modern C++ (11/14/17+) proficiency required.
• Adaptive-step numerical integration and linear algebra expertise.
• Multi-threading with std::thread and thread pools; race-condition avoidance.
• Manual memory management; seamless integration with third-party C/C++ libraries.
• Quaternion/rotation math and coordinate frame transforms.

Responsabilidades

• Write high-performance C++ code for adaptive-step numerical integration of physical systems.
• Ensure numerical accuracy and stability; manage third-party library integrations.
• Design cache-friendly data structures; implement multi-threaded execution models across cores.
• Explore intra-job CPU parallelism strategies (serial, OpenMP, MPI) as workload scales.
• Implement Kalman-filter-based state estimation fusing sensor measurements.

Conocimientos

C++ (modern)

Adaptive-step ODE

Multi-threading

Memory management

Quaternion math

Coordinate transforms

CMake

Unit testing

Python

Kalman filtering

Attitude dynamics

Astrodynamics

TLE familiarity

Herramientas

OpenMP

MPI/OpenMPI

Descripción del empleo

Functional Focus: High-Performance Computing, Numerical Methods, and Physics Simulation

• Simulation Engine Development: Write high-performance C++ code for adaptive-step numerical integration of physical systems, handling multiple perturbation/force models.
• Numerical Accuracy & Stability: Implement quaternion-based rotational dynamics and coordinate frame transformations, ensuring zero memory leaks when integrating third-party C/C++ scientific libraries.
• Shared-Memory Optimization: Design cache-friendly memory structures and multi-threaded execution models that avoid race conditions and false sharing across compute cores.
• Parallel Compute Strategy: Evaluate and implement intra-job CPU parallelism strategies — serial, shared-memory (e.g. OpenMP), or message-passing (e.g. MPI) —appropriate to workload scale.
• State Estimation: Implement Kalman-filter-based state estimation that fuses multiple sensor measurements — prediction, innovation, Jacobian assembly, and correction.

Mandatory:

• C++ (modern, 11/14/17+)
• Adaptive-step ODE/numerical integration, linear algebra
• Multi-threading (std::thread, thread pools), race-condition/false-sharing avoidance
• Manual memory management, leak-free integration with third-party C/C++ libraries
• Quaternion/rotation math, coordinate frame transforms
• CMake, unit testing (GoogleTest or similar)
• Python (for tooling/scripting/testing)
• Kalman/Bayesian filtering theory
• Attitude/rigid-body dynamics background
• Astrodynamics / orbital mechanics fundamentals
• TLE (Two-Line Element) format familiarity

Optional:

• OpenMP, MPI/OpenMPI
• Valgrind, AddressSanitizer, profilers (perf, VTune)
• CI pipelines for C++, cross-platform builds

We offer great career growth, ESOPs, Gratuity, PF and Health Insurance.