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hirly last saw it live on 1 September 2026. Similar roles are on the live board.

Higgsfieldai

ML Systems Performance Engineer (MFU)

Almaty, Kazakhstan

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Seniority
Mid level
Work mode
Remote-friendly
First seen by hirly
1 Sept 2026

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the posting

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 loading, 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.

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ML Systems Performance Engineer (MFU) at Higgsfieldai — hirly