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3 часа назад

Software Engineer, AI Training and Infrastructure (AI)

100 000 - 300 000$
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

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TL;DR
Software Engineer, AI Training and Infrastructure (AI): Building robust, scalable, and distributed training pipelines and frameworks for large-scale AI models in real-world robotics applications with an accent on data preprocessing, training orchestration, model evaluation, and resource optimization. Focus on integrating state-of-the-art machine learning techniques, identifying infrastructure bottlenecks, and ensuring reliability through automated testing and continuous integration.

Location: San Mateo, California, United States

Base salary: $100,000–$300,000 USD per year

Company

hirify.global develops general-purpose robotic intelligence that adapts to unseen scenarios using large-scale, data-driven machine learning.

What you will do

  • Develop and maintain robust, scalable, distributed training pipelines covering data preprocessing, training orchestration, and model evaluation.
  • Build frameworks and software infrastructure supporting the full machine learning lifecycle, from data preparation to model deployment.
  • Optimize training processes for performance, resource utilization, scalability, and reliability.
  • Collaborate with researchers and machine learning engineers to integrate state-of-the-art algorithms and techniques.
  • Monitor training systems, identify bottlenecks, and implement solutions to improve efficiency and performance.
  • Maintain infrastructure reliability through automated testing and continuous integration.

Requirements

  • BS, MS, or higher degree in Computer Science, Robotics, Engineering, or a related field, or equivalent practical experience.
  • At least 3 years of industry experience.
  • Proficiency in Python, C++, or a similar programming language, plus experience with a deep learning library such as PyTorch, TensorFlow, or JAX.
  • Strong background in distributed computing, parallel processing, large-scale datasets, and data preprocessing.
  • Deep understanding of state-of-the-art machine learning techniques, software engineering principles, algorithms, data structures, and system design.
  • Experience with cloud-based training environments, machine learning infrastructure, continuous integration, and automated testing frameworks.

Culture & Benefits

  • Work on robotic intelligence designed for deployment in real-world scenarios.
  • Collaborate with researchers and machine learning engineers on exploratory AI projects.
  • Join a team including new graduates, experienced engineers, and domain experts.

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