Senior GPU Software Engineer (Graphics / ML)

Luxoft Poland; Town of Poland (NY); Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Medical & Dental care

Life Insurance

Internal Mobility program

Job summary

Luxoft Poland is seeking hybrid engineers skilled in real-time graphics and machine learning to join a GPU software team. The role centers on rendering pipelines, ML model integration, and GPU performance optimization, collaborating with graphics and driver teams.

Successful candidates will handle both graphics and ML workloads, with hands-on experience in DX12/Vulkan and ML frameworks. Comfortable profiling, tuning, and delivering clean, testable code is required.

Qualifications

• 4+ years of professional software engineering experience (C++ primary; strong Python on the ML side).
• Solid GPU fundamentals: pipeline, synchronization and memory models, performance trade-offs.
• Ability to work in both GPU graphics and ML on images; cross-disciplinary experience.

Responsibilities

• Develop and optimize rendering and ML inference components for real-time visual pipelines (DX12, Vulkan, ONNX-based stacks).
• Profile GPU workloads and tune for latency, memory and throughput.
• Integrate ML models (super-resolution, denoising) into graphics pipelines.
• Evaluate output quality using objective and perceptual metrics (PSNR/SSIM, LPIPS) and visual regression tooling.
• Author clean, testable, reproducible code; collaborate with graphics, ML and platform teams.

Skills

C++

Python

GPU programming

Performance profiling

Tools

DX12

Vulkan

RenderDoc

Nsight

ONNX Runtime

TensorRT

Job description

Private Medical & Dental care & Life Insurance

Internal Mobility program - possibility of rotation between projects, locations, accounts

Project Description

We are looking for hybrid engineers - real-time graphics AND machine learning in one person - to join a GPU software team working at the intersection of rendering and image ML (upscaling, denoising, artifact suppression for interactive visual applications). The work spans rendering pipelines, ML model integration and GPU performance optimization, in collaboration with graphics and driver teams. Pure graphics engineers with no ML project experience, and ML engineers with no GPU/graphics programming experience, are not a fit for this role.

Responsibilities

Develop and optimize rendering and ML inference components for real-time visual pipelines (DX12, Vulkan, ONNX-based stacks).

Profile GPU workloads and tune for latency, memory and throughput.

Integrate ML models (super-resolution, denoising) into graphics pipelines.

Evaluate output quality using objective and perceptual metrics (PSNR/SSIM, LPIPS) and visual regression tooling.

Author clean, testable, reproducible code; collaborate with graphics, ML and platform teams.

Skills

What is relevant to have

4+ years of professional software engineering experience (C++ primary; strong Python on the ML side).

Solid GPU fundamentals: pipeline, synchronization and memory models, performance trade-offs.

BOTH areas below are mandatory - a profile covering only one of them is not a match:

(a) GPU / graphics programming: hands‑on production experience with DX12 and/or Vulkan (or CUDA/HIP GPU compute), shader/kernel authoring (HLSL/GLSL/compute), GPU debugging and profiling (RenderDoc, PIX, Radeon GPU Profiler, Nsight).

(b) ML on images: hands‑on project experience with PyTorch (or equivalent) on vision models - super‑resolution, denoising, artifact suppression, segmentation or comparable CNN/transformer work - including inference deployment and optimization on GPU (ONNX Runtime or TensorRT, quantization).

Depth may be asymmetric - deep expertise in one area plus solid practical project experience in the other is acceptable - but real project experience in BOTH is required. Graphics-only profiles with no ML project work, and ML profiles with no GPU/graphics programming (tabular / NLP / LLM-only data science), do not qualify.

Hands‑on performance profiling and optimization of real workloads.

What is nice to have

Ray tracing (DXR/VKRT), game engines (Unreal, Unity) or rendering middleware.

Color and image processing fundamentals (sRGB vs linear, HDR, resampling/filtering).

Render fidelity testing, SSIM/PSNR-based visual regression tooling.

CI-driven development, automated test harnesses.