cd /news/machine-learning/ml-systems-performance-engineer-mfu-… · home topics machine-learning article
[ARTICLE · art-109583] src=frontierroles.com ↗ pub= topic=machine-learning verified=true sentiment=· neutral

ML Systems Performance Engineer (MFU) — Higgsfield

Higgsfield AI, a generative AI company with $500M in annual revenue run rate and 25M+ users, is hiring an ML Systems Performance Engineer (MFU) for its Almaty, Kazakhstan office. The role focuses on optimizing distributed training performance, including MFU, tokens/sec/GPU, and scaling efficiency, with responsibilities spanning profiling, parallelism strategies, and CUDA/Triton kernel development. The position offers a competitive USD salary, equity, and relocation support, and requires on-site work five days per week.

read2 min views1 publishedAug 24, 2026
ML Systems Performance Engineer (MFU) — Higgsfield
Image: Frontierroles (auto-discovered)
  • Salary
  • Not published
  • Location
  • Almaty, Kazakhstan
  • Work type
  • On-site
  • Posted
  • today

Apply on company site (opens in new tab) Why work at Higgsfield AI?

Higgsfield AI is the fastest-scaling generative AI company in history, hitting $500M in annual revenue run rate, 25M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like.

What you will do

  • Profile end-to-end training runs and identify bottlenecks across compute, memory, communication, storage, and orchestration.
  • Define, measure, and improve MFU, tokens/sec/GPU, scaling efficiency, training goodput, and GPU uptime.
  • Optimize distributed training and model-sharding strategies, including data, tensor, pipeline, context, and expert parallelism.
  • Improve collective communication through topology-aware placement and compute/communication overlap.
  • Develop or integrate optimized CUDA and Triton kernels
  • Optimize data , preprocessing, sequence packing, and checkpointing so that I/O does not leave accelerators idle.
  • Diagnose distributed hangs фтв performance regressions.
  • Improve fault tolerance for long-running training jobs.

What we are looking for

  • Strong experience running and optimizing multi-GPU or multi-node training.
  • Experience with PyTorch Distributed or an equivalent training framework.
  • Understanding of GPU architecture, including memory hierarchy, Tensor Cores
  • Understanding of collective communication, cluster topology, and distributed-training bottlenecks.
  • Experience with distributed parallelism technologies such as FSDP, DeepSpeed, Megatron-LM, TorchTitan, or similar.
  • Ability to debug complex performance and reliability problems across multiple layers of the training stack.

Nice to have

  • CUDA, Triton or GPU-kernel development experience.
  • Experience with NCCL, MPI, UCX, RDMA, InfiniBand, RoCE, GPUDirect, NVLink, or NVSwitch.
  • Experience training Mixture-of-Experts, multimodal, or reinforcement-learning models.
  • Knowledge of PyTorch internals, torch.compile, XLA, ML compilers, or custom operators.
  • Experience with mixed-precision training, including BF16, FP8, or FP4.

What We Offer

  • Competitive base salary in USD, based on your experience, skills, and the scope of the role.
  • Equity participation through the company’s stock option program, giving you the opportunity to share in Higgsfield’s long-term growth.
  • Relocation support to Almaty for candidates moving from another city or country.
  • A highly collaborative, fast-paced environment where you can work directly with experienced leaders and have a meaningful impact on the product and company.
  • Opportunities for professional growth, ownership, and career development as the company scales.
  • Company-provided equipment, meals, transportation, or other office benefits.

This is a fully on-site role based in our Almaty office. Our team works from the office five days per week for the full working day. We believe in-person collaboration is an important part of how we move quickly, solve complex problems, and build strong teams.

── more in #machine-learning 4 stories · sorted by recency
── more on @higgsfield ai 3 stories trending now
sponsored brought to you by zahid.host 4,200+ EU-deployed projects
reading about agents? ship yours in a single git push.

Run your AI side-project on zahid.host

EU-based hosting, git-push deploys, automatic HTTPS, no cold starts. Free tier with a custom domain — perfect for shipping the agent you just read about.

$git push zahid main
Live at https://your-agent.zahid.host
Get free account → Pricing
from €0/mo · no card required
LIVE [news/ml-systems-performan…] indexed:0 read:2min 2026-08-24 ·