Job Overview
JOB DETAILS
Requirements
- 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.
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.
Desired 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.
Are you interested in this position?
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