Software Engineer, AI Training and Infrastructure

Skild AI

$100K — $300K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • BS, MS or higher in Computer Science, Robotics, Engineering, or equivalent experience.
  • Minimum 3 years of industry experience.
  • Proficiency in Python, C++, or similar languages, plus knowledge of at least one deep learning library.
  • Strong background in distributed computing and large-scale dataset handling.
  • Deep understanding of modern machine learning techniques and models.
  • Experience with cloud-based training environments like AWS or Google Cloud.
  • Practical knowledge of software engineering principles.

Responsibilities

  • Develop and maintain scalable training pipelines for AI models.
  • Optimize training processes for performance and resource efficiency.
  • Collaborate with researchers to integrate advanced algorithms into training systems.
  • Monitor training performance and troubleshoot bottlenecks.
  • Ensure reliability of training infrastructure through automated testing.

Benefits

  • Robust training and development programs.
  • Flexible work hours and remote work options.
  • Access to cutting-edge technology and tools.
  • Collaboration with innovative researchers in AI and robotics.
  • Supportive team culture focused on continuous improvement.
Full Job Description
Position Overview

We are looking for a Software Engineer to work at the forefront of developing and optimizing the software infrastructure and tools necessary for training cutting-edge AI models. You will focus on building robust, scalable, and efficient training pipelines and frameworks that support the entire machine learning lifecycle, from data preparation to model deployment. You will collaborate with researchers and machine learning engineers to ensure seamless integration and operation of training systems, pushing the boundaries of what AI can achieve in real-world robotics applications. You will explore new ways to efficiently make use of many types of data in our training pipeline.
Responsibilities
  • Develop and maintain robust, scalable, and distributed training pipelines (data preprocessing, training orchestration, and model evaluation) and frameworks for large-scale AI models.
  • Optimize training processes for performance and resource utilization, ensuring scalability and reliability.
  • 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 to improve efficiency and performance.
  • Ensure the robustness and reliability of the training infrastructure, including automated testing and continuous integration.
Preferred Qualifications
  • 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.
  • Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
  • 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.


Base Salary Range

$100,000-$300,000 USD

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