GPU Software Engineer (Graphics / ML)

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.

What we offer

• Global Relocation - (Relocation options; Experience in an international environment; Cross-cultural experience)

• Recognition and Evaluation - (Feedback culture; Regular appraisals)

• Time Off - (Annual holiday - 20 or 26 days. The duration of the leave depends on the overall seniority; Occasional leave - 1 or 2 days/ depending on the circumstances; Child care leave - 2 days or 16 hours per year; Absence due to force majeure - 2 days or 16 hours per year; Maternity Leave - 20 weeks; Parental Leave - 41 weeks; Paternity Leave - 14 days)

• Luxoft Training Center - (Expert-led tech courses covering basic to advanced topics; Internal instructor-led soft skills courses; Comprehensive in-house self-learning resources for both soft and hard skills; Access to external self-learning libraries like ProQuest eBook and Udemy for Business; Cloud Programs: MS Cloud Academy, AWS Partner Academy, Google Cloud Academy; Custom Learning Programs: upskilling, reskilling, technical mentorship; Leadership Programs for Managers)

• Well-being and Work-life Balance - (Multisport card; Possibility to order Multisport card at the corporate rate for family members; LuxGood Program: wellbeing seminars, contests, relaxation sessions, yoga sessions, etc.; One Team Program: Buddy for each New Joiner; seminars, meeting and workplace space to support integration with local community and culture; “Hire me” workshops for partners; Preferential banking offer; Preferential car leasing offer; Cafeteria program discounts for shops, cinema tickets, holiday offers; Luxoft Social Benefit Fund: sport and recreation benefits, the possibility to receive financial support)

• Health Care - (Private Healthcare Insurance with unlimited access to specialists; Full dental support; Travel Insurance; Possibility to add private healthcare coverage for family members at the corporate rate; Life insurance at the corporate rate for employees and family members, including payment of the basic package for the employee by the employer; Reimbursement for corrective glasses)

• Company Events and Friendly Environment - (Many fun social activities organized by the Luxoft team offline in your city; Online entertainment events for whole company and local team events; A workplace where you’re treated with respect within a multicultural team)

• Internal Mobility - (Rotation between projects and accounts; New career opportunities)

• Self-Learning Library

• CSR Projects

Other

• Languages: English: B2 Upper Intermediate

• Seniority: Senior

Requirements

• 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.

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

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

• CUDA/HIP compute experience.

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

• CI-driven development, automated test harnesses.

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.