EngineeringRemote

Research Engineer - AI Systems

Yotta Labs · Remote

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Last seen by MeritLog September 12, 2026Source: AshbySource version: ashby-public-job-posting-v1

MeritLog read this listing from Yotta Labs's Ashby job board and last checked it on September 12, 2026.

Source: the employer's Ashby job board. Open the original listing for current details.

Job details

Work model: Remote
Salary: Not listed by source
Location: United States

Hiring context

How this role compares at Yotta Labs

Yotta Labs has 4 live roles in MeritLog’s catalog across 2 job families, and 3 of them are in engineering. 0 of those listings publish a pay range, a disclosure rate of 0%.

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What you'd do

Design and implement high-performance kernels for Attention, MoE, GEMM, collective communication, and quantization.
Optimize kernels for NVIDIA, AMD, and AWS Trainium.
Develop custom operators and graph optimizations using Neuron SDK, PyTorch/XLA, Torch Dynamo, and Neuron Compiler.
Improve performance of vLLM, SGLang, TensorRT-LLM, and custom inference runtimes.
Design scalable distributed training and inference solutions across thousands of accelerators.
Contribute to open-source projects, publish technical findings and engage with the developer community.

What they're asking for

Proficiency in AI programming languages such as Python and C++.Skill
Deep understanding of GPU architecture and performance optimization.Skill
Experience with CUDA, Triton, ROCm/HIP, or AWS Neuron.Skill
Strong understanding of AI frameworks (e.g., PyTorch, Dynamo, LMCache), model architectures and profiling tools (e.g. Nsight, ROCm Profiler, or Neuron Profiler).Skill
Strong problem-solving skills and the ability to work in a collaborative, remote environment.Skill
A background in computer science, engineering, or a related field is preferred.SkillPreferred
Contributions to open-source AI infra projects like vLLM, SGLang, PyTorch, or Triton.SkillPreferred
Experience with with FlashAttention, PagedAttention, MoE, RLHF, or distributed AI systems.SkillPreferred
Publications in top-tier conferences like MLSys, OSDI, SOSP, NSDI, SC, HPCA, or ISCASkillPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

Location: Remote (Global) Type: Full-time Company: Yotta Labs Apply: careers@yottalabs.ai 🧠 About Yotta Labs Yotta Labs is building the next generation multi-silicon AI cloud and runtime platform to power the world’s most demanding AI workloads. We enable training and inference across NVIDIA GPUs, AMD GPUs, and AWS Trainium, helping AI companies achieve the best performance and economics across heterogeneous hardware. Our mission is to provide high-performance AI computing and Model API services, enabling AI companies, research labs, and enterprises to train, deploy and integrate cutting-edge models at scale. 🛠️ Role Overview We are seeking a highly motivated AI Systems Research Engineer specializing in Trainium, GPU kernels, and LLM systems optimization. You will work at the intersection of AI Systems, Compiler and Runtime Optimization, Distributed Training & Inference, GPU/Accelerator Kernel Development, and Large Language Model Infrastructure. Your work will directly impact the scalability and performance of AI applications deployed on our platform. 🎯 Responsibilities - Design and implement high-performance kernels for Attention, MoE, GEMM, collective communication, and quantization. - Optimize kernels for NVIDIA, AMD, and AWS Trainium. - Develop custom operators and graph optimizations using Neuron SDK, PyTorch/XLA, Torch Dynamo, and Neuron Compiler. - Improve performance of vLLM, SGLang, TensorRT-LLM, and custom inference runtimes. - Design scalable distributed training and inference solutions across thousands of accelerators. - Contribute to open-source projects, publish technical findings and engage with the developer community. ✅ Qualifications - Proficiency in AI programming languages such as Python and C++. - Deep understanding of GPU architecture and performance optimization. - Experience with CUDA, Triton, ROCm/HIP, or AWS Neuron. - Strong understanding of AI frameworks (e.g., PyTorch, Dynamo, LMCache), model architectures and profiling tools (e.g. Nsight, ROCm Profiler, or Neuron Profiler). - Strong problem-solving skills and the ability to work in a collaborative, remote environment. - A background in computer science, engineering, or a related field is preferred. 🌟 Preferred Experience - Contributions to open-source AI infra projects like vLLM, SGLang, PyTorch, or Triton. - Experience with with FlashAttention, PagedAttention, MoE, RLHF, or distributed AI systems. - Publications in top-tier conferences like MLSys, OSDI, SOSP, NSDI, SC, HPCA, or ISCA 🌐 Why Join Yotta Labs? - Be part of a visionary team aiming to redefine AI infrastructure and influence the future of multi-silicon AI computing. - Work on cutting-edge technologies that solves frontier AI infrastructure problems. - Collaborate with experts from leading institutions and tech companies. - Competitive compensation with equity. Enjoy a flexible, remote work environment that values innovation and autonomy. 📩 How to Apply Interested candidates should apply directly or send their resume and a brief cover letter to careers@yottalabs.ai. Please include links to any relevant projects or contributions.

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