3 часа назад
Software Engineer, AI Training and Infrastructure (AI)
100 000 - 300 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
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
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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