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1–2 jobs· newest first

Principal Engineer, Model Performance
Runware · Remote, US
Remote · Full-time · Principal
Senior Machine Learning Engineer, Inference
AIDA Recruitment · Mountain View, US+5 more
$250K–$300KHybrid · Full-time · SeniorVisa

+10K new in the last hour

Principal Engineer, Model Performance

Runware · Posted Nov 6, 2026

Remote, United States
Remote
Full-time · Principal
10+ years

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AI

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Lead inference performance for Runware’s AI Factory, owning kernel development, benchmarking, and team leadership across GPU, HPC, and deep learning systems.

Responsibilities

Own inference performance end to end for the fleet
Set the model performance roadmap
Write and tune CUDA kernels, fuse attention and MLP paths
Build pipelines for new model deployment
Choose and shape the serving stack

Requirements

Nice to have: Diffusion and video generation performance
Nice to have: DiT
Nice to have: UNet pipelines
Nice to have: LoRA hot-swapping
Nice to have: ComfyUI

Skills

CUDA C++Python PyTorch Triton Nsight Systems Nsight Compute TensorRT-LLM vLLM SGLang NCCL CUDA Graphs Tensor Cores GPU architecture GPU memory hierarchy quantization speculative decoding continuous batching paged KV cache pipeline parallelism expert parallelism FlashAttention CUTLASS Dynamo

Benefits

Meaningful stock options
Generous paid time off
Vacation
Sick days
Public holidays

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Senior Machine Learning Engineer, Inference

AIDA Recruitment · Posted Nov 5, 2026

Mountain View, California, United States +5 more
Hybrid
Full-time · Senior
$250K–$300K per year
5+ years
Visa sponsorship

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Senior Machine Learning Engineer focused on ML inference optimization for realtime voice and LLM technology.

Locations (6)

Mountain View, California, United States
Canada
United Kingdom
Germany
Switzerland

Serbia

Compensation

Salary: $250K–$300K base + competitive equity

Responsibilities

Own inference optimization end-to-end, from research to production deployment
Optimize latency and throughput of realtime voice and LLM inference at consumer scale
Work inside inference engines such as vLLM, TRT-LLM and SGLang
Apply model acceleration techniques – quantization, distillation, speculative decoding, caching, continuous batching and paged attention
Write high-performance code in C++, CUDA, Rust or optimized Python for GPU workloads

Requirements

PhD in Computer Science, Physics or Mathematics, or a degree from a top CS program
Nice to have: open-source inference engine contributions
Nice to have: technical write-ups

Skills

ML inference optimization C++CUDA Rust Python vLLM TRT-LLM SGLang Kubernetes Ray quantization distillation speculative decoding continuous batching paged attention

Benefits

competitive equity
relocation assistance to the San Francisco Bay Area

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