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1–2 jobs· newest first

ML Research EngineerNew
Microsoft · Redmond, US
$102K–$202K
Sr. Software Engineer, Training/Inference (C++)
SpaceXAI · Palo Alto, US
$220K–$357KFull-time · Senior

+10K new in the last hour

ML Research Engineer

Microsoft · Posted Nov 11, 2026

Redmond, Washington, United States
$102K–$202K per year
1+ years

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AI

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Compensation

The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800 - $219,200 per year.

Responsibilities

Design and develop novel quantization and numerics algorithms to enable efficient deployment of LLM inference and training in Microsoft’s Azure production environments.
Drive software development and model optimization tooling proof-of-concept effort to streamline deployment of quantized models.
Analyze performance bottlenecks in quantized state-of-the-art LLM architectures and drive performance improvements.
Prototype and evaluate emerging low-precision data formats through proof-of-concept implementations on novel hardware accelerator SDK.
Co-design model architecture optimized for low-precision deployment in close collaboration with companywide AI/ML teams.

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
Nice to have: publications (patents, peer-reviewed academic papers)
Nice to have: large-scale model evaluation

Skills

statistics predictive analytics research model compression low-precision numerics low-level kernel development performance optimization PyTorch TensorFlow TensorRT ONNX Runtime CUDA Triton ROCm Python C

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Sr. Software Engineer, Training/Inference (C++)

SpaceXAI · Posted Nov 6, 2026

Palo Alto, California, United States
Full-time · Senior
$220K–$357K per year
5+ years

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Design and optimize large-scale model serving systems for Grok, including distributed infrastructure, GPU kernel work, and low-level optimizations.

Compensation

$220,000 - $357,000 USD

Responsibilities

Architect and implement scalable distributed infrastructure for model serving (load balancing, auto-scaling, batch scheduling, global KV cache)
Optimize latency and throughput of model inference under real production workloads
Build and operate high-concurrency serving systems with excellent tail latency and high reliability at the scale required to serve millions of users
Benchmark, fine-tune, and accelerate inference engines (including low-level GPU kernel work and code generation)
Develop custom tools to trace, replay, and fix issues across the full stack — from orchestration down to GPU kernels

Requirements

Bachelor’s degree in computer science, computer engineering, or science discipline
Nice to have: Experience with large-scale, high-concurrent production serving
Nice to have: Experience with GPU inference engines (e.g., vLLM, SGLang, Triton, TensorRT-LLM)
Nice to have: Strong background in system optimizations: batching, caching, load balancing, parallelism
Nice to have: Low-level inference optimizations: GPU kernels, code generation

Skills

C/C++Rust low-level system programming GPU inference engines system optimizations batching caching load balancing parallelism GPU kernels code generation quantization speculative decoding distillation low-precision numerics testing benchmarking reliability CI/CD infrastructure vLLM SGLang Triton TensorRT-LLM

Benefits

equity
comprehensive medical coverage
vision coverage
dental coverage
401(k) retirement plan

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