Research Scientist / Engineer – Performance Optimization
Luma AI is hiring a Research Scientist / Engineer – Performance Optimization for a remote role open to applicants in United States. Level rates it ; you can apply on Luma AI.
Level's read on this job
- Level rates this research scientist role Builds AI ●●●●: the job is building AI systems.
- The posting lists this role as remote.
- Tools and skills the posting cites include PyTorch, Triton and CUDA.
- Level classifies it as a senior role.
- Level lists 29 other open roles at Luma AI.
AI in this role
Profile and optimize GPU code, write custom fused kernels, and accelerate transformer models for training and deployment.
You'll make Luma's multimodal models fast — profiling and optimizing GPU, CPU, and accelerator code so they train efficiently and deploy at scale without sacrificing quality. You'll write the kernels and operations that get the most out of the hardware.
This is deep performance work: fused kernels, tensor cores, Triton and CUDA, distributed multi-node deployment. It fits someone with expert GPU-optimization skills and a deep understanding of transformer internals. If you're not at home in CUDA, Triton, and profilers, this is the wrong depth.
What You'll Own
Profile and optimize GPU/CPU/accelerator code for maximum utilization and minimal latency.
Write high-performance PyTorch, Triton, and CUDA, dropping to custom operations when needed.
Develop fused kernels and leverage tensor cores and modern hardware features across platforms.
Optimize model architectures and implementations for distributed multi-node production deployment.
Build performance monitoring and analysis tools and automation.
Research and implement cutting-edge optimization techniques for transformer models.
First 90 Days
One way the first 90 could unfold.
Days 1–30 — Immerse & Diagnose: Profile the current training and inference paths and find the biggest performance wins.
Days 30–60 — Ship & Validate: Land a kernel or architecture optimization that measurably improves utilization or latency.
Days 60–90 — Scale & Systemize: Build the monitoring and automation that keeps performance gains from regressing.
What You Bring
Expert-level Triton/CUDA programming and GPU optimization.
Strong PyTorch skills, including kernel development and custom operations.
Proficiency with profiling tools (NVIDIA Nsight, torch profiler, custom tooling).
Deep understanding of transformer architectures and attention mechanisms.
Nice to Have
Experience with compilers and exporters (torch.compile, TensorRT, ONNX, XLA).
Experience optimizing inference workloads for latency and throughput.
Triton compiler and kernel fusion techniques.
Knowledge of warp-level intrinsics and advanced CUDA optimization.
About Luma: Luma's mission is to build unified general intelligence that can generate, understand, and operate in the physical world. We believe multimodality is critical for intelligence — the next step beyond language models comes from vision. Luma is an equal opportunity employer.
How we rate this
Research Scientist / Engineer – Performance Optimization at Luma AI rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in research scientist jobs at this level
Pay
- Typical research scientist job
- $192k
This posting doesn't list pay. Use the typical research scientist figure when pay comes up. See research scientist jobs
Questions you could be asked
- Tell me about a project where gpu optimization was part of your work. What did you do?
- Tell me about a project where kernel development was part of your work. What did you do?
- Tell me about a project where performance profiling was part of your work. What did you do?
- Tell me about a project where transformer architectures was part of your work. What did you do?
- Walk me through how you've used PyTorch in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: GPU Optimization, Kernel Development, Performance Profiling, Transformer Architectures, and PyTorch. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get new remote research scientist jobs (Builds AI ●●●●) by email
One email a week with the new remote research scientist jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Research roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step