Referso Jobs

ML Infrastructure Engineer

Nebius · Posted May 12, 2026

Open

Remote, Netherlands +2 more
Remote
Full-time
Competitive compensation

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ML Infrastructure Engineer

Nebius · Posted May 12, 2026

Open

Remote, Netherlands +2 more
Remote
Full-time
Competitive compensation

Apply with Referso

Senior AI Research Engineer - GPU Systems & Kernels

Datadog · Posted Nov 9, 2026

Open

Paris, Île-de-France, France
Hybrid
Senior

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Lead GPU kernel development and optimization for large-scale AI model training and inference.

Responsibilities

Write, tune, and debug GPU kernels (CUDA, Triton, or similar) for LLM training and inference
Optimize for latest NVIDIA GPU generations, memory hierarchy, tensor cores, and low-precision formats
Reduce communication cost in distributed workloads and overlap communication with compute
Profile end-to-end training and rollout workloads to identify bottlenecks
Build benchmarks, profiling tools, and regression tests

Requirements

Nice to have: Mixture-of-Experts models
Nice to have: expert parallelism
Nice to have: sparse model inference
Nice to have: distributed training frameworks
Nice to have: graphics rendering

Skills

GPU kernel development CUDA Triton C++Rust Python

Staff Machine Learning Engineer

Unity Technologies · Posted Jul 15, 2026

Open

Remote, United States
Remote
Staff
$218K–$284K per year
5+ years

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Senior Machine Learning Engineer for On-Device & Mobile AI

Compensation

Salary range : 218 400.00 USD - 283 900. 00 USD

Responsibilities

Own the optimization pipeline for the models you ship
Apply quantization, weight sharing, pruning, and distillation
Do low-level performance work: write and tune WebGPU compute shaders and native kernels
Profile with browser and platform tools and eliminate bottlenecks
Build parts of the integration between the ML runtime and the game engine

Skills

machine learning on-device optimization quantization model export ONNX Runtime WebGPU Metal Vulkan CUDA Python

Sr. Software Engineer, Kernels/CUDA (C++)

SpaceXAI · Posted Nov 6, 2026

Open

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

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Design, build, and optimize massive GPU clusters for extreme-scale training and inference workloads; develop and tune low-level CUDA kernels; profile, debug, and eliminate bottlenecks across GPU memory hierarchy, networking fabric, filesystems, and multi-GPU operation; collaborate closely with AI research teams to deliver production-grade performance and scalability.

Compensation

$220,000 - $357,000 USD

Responsibilities

Design, build, and optimize massive GPU clusters for extreme-scale training and inference workloads
Develop and tune low-level CUDA kernels (GeMM, Attention, etc.), using CUTLASS, Tensor Cores, and Nsight for maximum performance
Profile, debug, and eliminate bottlenecks across GPU memory hierarchy, networking fabric, filesystems, and multi-GPU operation
Collaborate closely with AI research teams to deliver production-grade performance and scalability

Requirements

Nice to have: Deep low-level systems programming
Nice to have: Strong experience with large-scale GPU clusters or distributed compute infrastructure at production scale
Nice to have: Hands-on work with GPU kernel optimization
Nice to have: Track record of building or running high-performance infrastructure for AI workloads
Nice to have: Ability to reason from first principles and optimize for both memory-bound and compute-bound scenarios

Skills

C/C++

Fellow, AI Workload Optimization

Advanced Micro Devices, Inc · Posted Nov 5, 2026

Open

San Jose, California, United States
Senior

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Lead end-to-end AI workload optimization strategy, driving performance across AMD’s AI software stack.

Responsibilities

Set the technical vision and roadmap for workload optimization across the AI software stack
Lead the profiling, analysis, and tuning of large-scale models to ensure out-of-the-box performance on AMD hardware
Partner with top customers and hyperscalers to understand unique workload requirements and deliver tailored architectural wins and software optimizations
Collaborate across hardware architecture, compiler, and framework teams to influence future silicon features
Drive the development of advanced tools and frameworks for performance estimation, modeling, and automated reporting

Requirements

PhD or Master’s degree in Computer Science, Electrical Engineering, or related field
Nice to have: High-level technical leadership
Nice to have: AI frameworks (PyTorch, JAX, vLLM, SGLang)
Nice to have: ROCm software stack
Nice to have: TorchProfiler

Skills

AI hardware architecture software optimization performance profiling tools

Senior / Staff AI Research Engineer, Real-Time Inference

RoboForce · Posted Nov 5, 2026

Open

Milpitas, California, United States
On-site
Full-time · Senior
$185K–$325K per year
4+ years
Visa sponsorship

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Lead end‑to‑end optimization of embodied AI inference pipelines for edge robotics.

Compensation

Compensation: Salary $185,000–$325,000 USD + Bonus + Equity

Responsibilities

Develop and optimize inference pipelines for embodied AI models targeting real‑time execution on edge hardware
Implement CUDA‑level optimizations including custom kernels, memory layout tuning, and hardware‑aware graph compilation
Apply and advance model compression techniques to achieve production‑grade throughput on constrained devices
Profile and debug end‑to‑end inference stacks using tools such as NSight, TensorRT, and Triton
Collaborate with ML research and robotics teams to co‑design model architectures that meet real‑time control‑loop latency requirements

Requirements

Master's degree in Computer Science, Electrical Engineering, or related field
PhD degree
Nice to have: embodied AI models (VLA, multimodal transformers, diffusion‑based policies)
Nice to have: compiler‑based optimization pipelines such as XLA, torch.compile, MLIR
Nice to have: understanding of robotics system constraints

Skills

CUDA programming GPU architecture

ML Infrastructure Engineer

ML Infrastructure Engineer

Locations (3)

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Senior AI Research Engineer - GPU Systems & Kernels

Responsibilities

Requirements

Skills

Staff Machine Learning Engineer

Compensation

Responsibilities

Skills

Sr. Software Engineer, Kernels/CUDA (C++)

Compensation

Responsibilities

Requirements

Skills

Fellow, AI Workload Optimization

Responsibilities

Requirements

Skills

Senior / Staff AI Research Engineer, Real-Time Inference

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Nsight jobs

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