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Research Engineer (AI)

210 000 - 320 000$
Тип работы
fulltime
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
Research Engineer (AI): Developing novel model architectures, training objectives, and distributed training systems for large-scale deep learning with an accent on algorithmic efficiency, GPU cluster utilization, and data pipelines. Focus on reproducing and extending state-of-the-art research, optimizing communication and training performance, and translating mathematical concepts into reliable production code.

Location: San Mateo or New York, United States

Salary: $210,000–$320,000 per year, plus equity

Company

hirify.global provides a platform for building, training, and serving specialized AI models across text, image, embedding, audio, and multimodal workloads.

What you will do

  • Explore new model architectures, training objectives, and optimization techniques through hypothesis-driven experiments.
  • Implement and reproduce results from recent machine learning research, identify limitations, and extend methods to larger datasets and models.
  • Design, implement, and maintain high-performance distributed training systems for large GPU clusters.
  • Optimize training loops, data loaders, communication overhead, and GPU cluster utilization.
  • Translate mathematical research concepts into clean, reliable, and efficient code.
  • Collaborate with research scientists on tooling, hardware-aware experiments, and infrastructure improvements.

Requirements

  • Strong programming skills in Python, C++, or Rust.
  • Practical knowledge of PyTorch, JAX, or TensorFlow.
  • Experience with distributed systems and parallel computing, including technologies such as CUDA, NCCL, or MPI.
  • Strong foundation in linear algebra, calculus, probability, and statistics.
  • Experience implementing complex deep learning algorithms from scratch.
  • Work location: San Mateo or New York, United States.

Nice to have

  • Master’s or PhD in computer science, machine learning, physics, mathematics, or a related field, or equivalent industry experience.
  • Experience with CUDA, Triton, or hardware co-design.
  • Familiarity with large language model training.
  • Familiarity with inference and inference engines such as SGLang and vLLM.

Culture & Benefits

  • Work on AI infrastructure, including low-latency inference and scalable model serving.
  • Build production AI technology using open models across multiple modalities.
  • Collaborate with engineers and AI researchers on high-impact technical problems.
  • Equity is included in the compensation package.
  • Inclusive, equal-opportunity working environment.

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