ML Engineer with Image Upscaling Experience

We are looking for an ML Engineer with hands-on image upscaling (single-image super-resolution) experience to build and ship production-quality upscaling and artifact suppression models for real-time / interactive visual applications. The work combines computer vision, perceptual quality optimization, and GPU-focused deployment, with integration into graphics stacks and strong engineering practices (reproducibility, CI/CD, benchmarking, telemetry). Develop and improve single-image super-resolution and artifact suppression models (noise, compression artifacts, ringing, halos) Optimize quality using a balanced approach between PSNR/SSIM and perceptual quality (e.g., LPIPS) Build efficient training and data pipelines (incl. mixed precision, distributed training when needed) Deploy and optimize models for GPU / edge inference (latency, memory, throughput) Integrate ML components into graphics/visual pipelines (coordination with graphics/engine teams) Run rigorous benchmarking and maintain model quality/perf dashboards; document design decisions and trade-offs Collaborate cross-functionally with graphics, product, QA, and platform teams