AI Engineer - Machine Learning 2
The following information aims to provide potential candidates with a better understanding of the requirements for this role.
Join our team as a Machine Learning Engineer and play a pivotal role in advancing our software foundation and tools essential for training cutting-edge AI models. You'll develop scalable and efficient training infrastructures, collaborate with researchers and engineers, and push the boundaries of AI in practical robotics applications—think robots that can fold laundry or assemble engines! If you're passionate about innovative methods for leveraging diverse datasets and want to work with leading robotics companies and top researchers, we invite you to apply and help shape the future of AI in real-world scenarios.
Responsibilities:
• Create and uphold efficient, scalable, and distributed training systems—including data preprocessing, training orchestration, and model assessment—for training large-scale AI models.
• Enhance the efficiency of training procedures to improve performance and use of resources, while maintaining scalability and dependability.
• Collaborate with researchers to create training and evaluation pipelines for state-of-the-art algorithms.
• Develop and design benchmarks for evaluating ML models.
• Perform training and and fine-tuning of foundation models for robotic applications .
• Monitor and analyze pipelines, 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.
• 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.
Top Hard Skills Required + Years of Experience:
1. Minimum 2+ years experience with Linux
2. Minimum 2+ years experience with Python
3. Minimum 2+ years experience with Configuration management.
4. Minimum 2+ years experience with ROS/ROS2,
5. Minimum 2+ years experience with TensorFlow.
6. Minimum 2+ years experience with any sort of machine learning packages.
Type: Contract
Work Schedule: Hybrid
Duration: 7.5 months, with a chance of extension
Hourly Rate Range: $85-100/h