ML Systems Performance Engineer (MFU)

5 дн. назад

KazakhstanCISSeniorOnsite

pytorchcudatritondistributed trainingmodel parallelismperformance profiling

Optimize and improve performance of multi-GPU distributed training systems for generative AI models.

• 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.

• 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.

• 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.

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.

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.