GPU Software Engineer (m/f/d) – CUDA / Numerical Methods / Energy Sector

Job@ctive GmbH; Köln; Remote; EUR 70.000 - 90.000; Vollzeit

Zusammenfassung

A leading energy-sector company is seeking an experienced GPU Software Engineer to optimize power flow calculations and numerical simulations on NVIDIA GPUs. The role requires strong expertise in CUDA development and numerical linear algebra, along with proficiency in NVIDIA libraries and tools. This position offers flexible start dates and a remote working arrangement for skilled candidates.

Qualifikationen

• Strong experience in CUDA development including custom kernels and memory management.
• Background in numerical linear algebra with matrix operations expertise.
• Very good English communication skills.

Aufgaben

• Porting and optimizing power flow calculations to run on NVIDIA GPUs.
• Designing high-performance CUDA kernels for matrix operations.
• Profiling GPU execution using NVIDIA tooling.

Kenntnisse

CUDA development

Numerical linear algebra

GPU-accelerated libraries (cuBLAS, cuSOLVER, cuSPARSE)

NVIDIA debugging/profiling tools

HPC concepts

English communication skills

Tools

NVIDIA Jetson

Python bindings (Numba/cuPy)

Jobbeschreibung

Project Overview

A leading energy-sector company is looking for an experienced GPU Software Engineer with strong expertise in CUDA, GPU-accelerated numerical computation, and matrix operations.

The project focuses less on LLM/AI topics and instead centers on power flow calculations and large-scale numerical simulations that must be efficiently executed on NVIDIA GPUs.

You will work on porting, optimizing, and accelerating computational code onto CUDA, leveraging frameworks such as cuBLAS, cuSOLVER, cuSPARSE, or similar, as well as NVIDIA tooling (incl. QDSS, Jetson toolchain if relevant).

Key Responsibilities

• Porting and optimizing power flow / power system calculations to run on NVIDIA GPU hardware

• Designing and implementing high-performance CUDA kernels for matrix operations and numerical solvers

• Profiling and optimizing GPU execution using NVIDIA tooling (e.g., qdss, Nsight Systems/Compute)

• Working with large-scale matrix algebra, linear equation solving, iterative solvers, and sparse/dense matrix handling

• Adapting existing CPU-based simulation code to GPU environments

• Ensuring numerical stability and precision in GPU-accelerated computation

• Close collaboration with power system engineers and simulation experts

• Documentation and handover of GPU-optimized modules

• Optional: contribution to Jetson-based environments if needed

Required Skills

• Strong experience in CUDA development (custom kernels, memory management, warp optimization)

• Background in numerical linear algebra, matrix operations, and solving systems of equations

• Experience with GPU-accelerated libraries such as:

  • cuBLAS, cuSOLVER, cuSPARSE, Thrust, or similar

• Knowledge of NVIDIA debugging/profiling tools (e.g., qdss, Nsight)

• Solid understanding of HPC concepts (parallelization, compute efficiency, memory hierarchy)

• Ability to work independently in a nearshoring/remote setup

• Very good English communication skills

Nice to Have

• Experience with power flow calculations, electrical grid simulation, or energy modeling

• Experience with NVIDIA Jetson platforms

• Familiarity with Python bindings (Numba/cuPy) or C++ integration

• Background in energy sector or critical infrastructure

• Knowledge of GPU cluster environments

Project Conditions

• Start: Flexible, ideally soon

• Duration: 6+ months with likely extension

• Mode: Remote / nearshore-friendly

• Onsite: Not required regularly

• Language: English