Description

You will build and maintain scalable, distributed training systems for large-scale AI models. You design benchmarks for model evaluation and collaborate with researchers to develop training and evaluation pipelines for state-of-the-art algorithms.

Responsibilities

• Orchestrate data preprocessing, training, and model assessment for distributed systems.
• Optimize training procedures to improve performance and resource utilization while ensuring scalability.
• Develop and design benchmarks for evaluating machine learning models.
• Perform training and fine-tuning of foundation models for robotic applications.
• Monitor pipelines to identify bottlenecks and implement solutions for efficiency.

Required Skills

• 5+ years of experience in AI Engineering or Machine Learning.
• Proven ability to create efficient, scalable, and distributed training systems.
• Experience with large-scale AI model training and fine-tuning.
• Strong understanding of data preprocessing and training orchestration.
• Ability to design and implement evaluation benchmarks.
• Experience with continuous integration and automated testing for ML infrastructure.
• Background in working with researchers to deploy state-of-the-art algorithms.

Key Skills

Education

Any Graduate