Software Engineer, AI Training and Infrastructure

The role

You will develop and maintain robust, scalable, and distributed training pipelines and frameworks for large-scale AI models. You will optimize training processes and collaborate with researchers to integrate algorithms into training pipelines.

What you will do

• Develop and maintain robust, scalable, and distributed training pipelines and frameworks for large-scale AI models.
• Optimize training processes for performance and resource utilization.
• Collaborate with researchers and machine learning engineers to integrate state-of-the-art algorithms and techniques into training pipelines.
• Monitor and analyze training, identifying bottlenecks and proposing solutions.
• Ensure the robustness and reliability of the training infrastructure, including automated testing and continuous integration.

Required qualifications

• Proficiency in Python, C++, or similar.
• At least one deep learning library such as PyTorch, TensorFlow, JAX, etc.

Nice to have

• BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
• Minimum of 3 years of industry experience.
• Strong background in distributed computing, parallel processing techniques, handling large-scale datasets and data preprocessing.
• Deep understanding of state-of-the-art machine learning techniques and models.
• Experience with cloud-based training environments (AWS, Google Cloud, Azure).
• Experience in developing and maintaining software tooling and infrastructure for machine learning.
• Deep understanding and practical experience with software engineering principles, including algorithms, data structures, and system design.
• Experience with continuous integration and automated testing frameworks.

About the company

Skild AI is building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. The team consists of individuals with varying levels of experience and backgrounds.