Description

You will bridge AI research and engineering by training large-scale foundational models, taking full ownership of the model lifecycle to power the company's autonomous capabilities.

Requirements

• •MSc or PhD in Machine Learning, Computer Science, or Mathematics
• •Theoretical understanding and practical experience in training Foundational Models
• •Strong software engineering skills in Python and modern DL frameworks
• •Ability to write custom layers, loss functions, and distributed training loops
• •Clear communication and contribution to research culture
• •First-principles mindset and ability to implement ArXiv papers
• •Top-tier research track record with authored publications
• •Experience training models on large-scale GPU clusters
• •Proven experience in data curation and building robust data pipelines

Tasks

• •Research and design large-scale Foundational Models
• •Train and fine-tune Vision-Language Models
• •Transform multimodal sensor data into autonomous capabilities
• •Manage the entire model lifecycle
• •Curate, clean, and prune large-scale datasets
• •Build robust data pipelines
• •Develop custom layers and loss functions
• •Implement distributed training loops
• •Evaluate model performance and effectiveness
• •Train models on large-scale GPU clusters
• •Publish research on attention mechanisms and transformers

Tools & Technologies

Benefits