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A seasoned Senior ML Engineer who drives distillation of ML Models for high-performance, production-ready rendering systems. You are passionate about software engineering and possess leadership skills to drive sophisticated issues to resolution. Able to communicate effectively and work optimally with different teams across AMD.
Data and training: large-scale dataset curation, synthetic data generation, curriculum learning, augmentation strategies
MLOps: experiment tracking, CI/CD for models, model registries, reproducibility, telemetry
Integrate ML inference into production rendering pipelines: define model I/O, preprocessing/postprocessing, and make trade-offs for latency, throughput, and quality
Collaborate across teams (ML researchers, engine/platform, tooling, QA) to translate ML and product requirements into graphics-friendly implementations and integration plans
Mentor other engineers, conduct code reviews, and help define best practices for rendering, performance, and SDK delivery
Requirements:
6–10+ years in ML engineering or applied research
3+ years focused on model distillation/compression at production scale
Strong proficiency in PyTorch (preferred) or JAX/TF
Ability to implement custom training loops, distributed training, and mixed precision
Demonstrated experience shipping distilled or compressed models to production with measurable gains in latency/memory and maintained quality
Deep understanding of knowledge distillation techniques: teacher–student frameworks, soft-labels, intermediate feature matching, contrastive distillation, task-specific loss shaping
Hands-on experience with quantization (static/dynamic, PTQ/QAT), pruning, and graph-level optimizations (operator fusion)