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14 часов назад

ML Performance Engineer (AI)

100 000 - 150 000$
Формат работы
remote (только USA)
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
ML Performance Engineer (AI): Optimizing end-to-end training and inference pipelines for large neural network systems with an accent on throughput, latency, cost efficiency, and GPU performance. Focus on distributed training, LLM serving, compiler-level optimization, custom kernels, and rigorous benchmarking across production workloads.

Location: 100% remote within the United States; the posting also lists Plymouth, MN.

Salary: $100,000–$150,000 annually

Company

hirify.global is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

What you will do

  • Profile and optimize AI training and inference pipelines for throughput, latency, and cost.
  • Identify bottlenecks across data loading, model computation, communication, memory, storage, and distributed systems.
  • Implement model compression, quantization, sparsity, pruning, KV-cache optimization, continuous batching, and speculative decoding.
  • Optimize distributed training and inference using tensor parallelism, pipeline parallelism, FSDP, and ZeRO-style sharding.
  • Drive compiler and kernel-level improvements with Triton, XLA, TorchInductor, TVM, and related technologies.
  • Build benchmark and regression frameworks, evaluate new hardware and software, and share performance playbooks across engineering teams.

Requirements

  • Six or more years of experience in performance engineering, ML systems, or HPC.
  • Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.
  • Strong proficiency in Python and C++.
  • Hands-on experience optimizing deep learning workloads on modern GPUs.
  • Deep understanding of distributed training, inference, memory hierarchies, communication primitives, and parallelism strategies.
  • Experience with CPU, GPU, and distributed-system profiling, along with strong measurement, debugging, analytical, communication, and collaboration skills.

Nice to have

  • Production-scale LLM inference optimization experience.
  • Contributions to vLLM, TensorRT-LLM, DeepSpeed, or similar projects.
  • Custom kernel authoring with Triton or CUTLASS.
  • FinOps experience for AI workloads.
  • Publications or talks on AI systems performance.

Culture & Benefits

  • Full-time direct W-2 employment.
  • Collaboration with product, design, engineering, operations, and business stakeholders.
  • Opportunities to contribute to production AI systems, engineering standards, code reviews, design reviews, and mentorship.
  • Career growth within an established technology consulting and software development organization.
  • Applicants must be authorized to work in the United States; new H-1B visa petitions cannot be sponsored.

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