layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

LAYIQ - Principal AI Product Engineer at Nscale

10–15 years of engineering experience, with a clear track record of pillar-level impact on production AI systems
4+ years of hands-on work with LLMs in inference, GPU performance, evals, or post-training and RL, in production or research
Demonstrated ability to define multi-year technical strategy for complex, multi-team AI systems organizations
World-class depth in production LLM inference, GPU performance, evals, and/or post-training and RL infrastructure, with strong working knowledge across the rest
Demonstrated ownership of the architecture of a large-scale production inference or training platform
Proven ability to create architectural frameworks and engineering standards adopted across large engineering organizations
Deep understanding of the hardware/software boundary for AI accelerators: CUDA or ROCm, memory bandwidth and interconnect constraints, and distributed compute paradigms
Strong history of growing technical leaders (Staff and above) and multiplying technical capability across teams
External recognition in the AI systems community through research, open source, or industry contribution
Preferred
Prior experience at a top-tier AI lab or major hyperscaler AI infrastructure team
Maintainer or core contributor to a foundational inference, kernel, or RL framework (vLLM, SGLang, TensorRT-LLM, LMCache, FlashInfer, Triton, verl, OpenRLHF, TRL, DeepSpeed, Megatron-LM, etc.)
Hands-on depth in RL for LLMs (DPO/GRPO-style methods, reward modelling, multi-turn and tool-use RL) and the interaction between inference and training infrastructure
Experience defining developer API platforms adopted at scale by external developers
Deep experience with control plane / data plane architecture and cell-based deployment patterns in large-scale inference infrastructure
Published work in AI systems: MLSys, NeurIPS Systems Track, OSDI, EuroSys, SC, or equivalent
Experience with hardware-software co-design: custom accelerator kernels (CUDA, Triton), compiler-level optimization, AI hardware roadmap engagement
Experience defining pricing, SLO, and capacity models for a commercial inference product
The range below reflects the base salary for the position. Actual compensation may vary based on job-related factors such as skill set, experience, education, and location. In addition to base salary, this role may be eligible for bonus, equity, and/or commission programs. Nscale may offer a competitive benefits package including medical, dental, vision, flexible paid time off, parental leave, and retirement plan participation.

Principal AI Product Engineer

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