About this role
As a Member of Technical Staff in AI Systems, Model Optimization, develop the training methods, optimization strategies, and infrastructure needed to run AI models efficiently on Unconventional’s novel, physics-based compute substrates. The role connects model architecture to physical silicon and tapeout. The posting lists Mountain View, CA and US Remote as locations.
Responsibilities
- Build performance models and energy benchmarks that assess compute, memory, and energy trade-offs and track Pareto-optimal model and hardware configurations.
- Partition and map complex AI models to hardware. Develop quantization, sparsity, pruning, and distillation approaches suited to the substrates’ physical constraints.
- Apply quantization-aware, noise-aware, and sparsity-focused training to address analog compute constraints, including memory footprint, connectivity, precision, and noise.
- Develop and optimize GPU kernels with low-level tools such as CUDA, Triton, or CUTLASS; profile and debug training and inference bottlenecks in complex ML codebases.
- Translate model requirements into specifications for hardware and infrastructure teams and document findings for tapeouts.
Minimum qualifications: An MS/PhD or equivalent research or project experience in a quantitative field such as AI/machine learning, computer science, physics, electrical engineering, or applied math. Requires practical knowledge of the modern AI/ML stack, optimized GPU execution, performance profiling, and the system implications of architectures such as Transformers, Mixture of Experts, and diffusion models. Deep PyTorch experience is required, including its internals, torch.compile, DDP, and FSDP.
Preferred qualifications
Experience with production training frameworks such as Megatron-LM or DeepSpeed and large-scale distributed training; interest in co-designing training systems around unconventional hardware physics; and research or practical work on advanced compression or approximation, including noise-aware or physics-constrained training.
Stated benefits include health benefits, 401(k) matching, unlimited PTO, and complimentary meals in the Palo Alto office.