Member of Technical Staff, Machine Learning - NomadicML

The role

This person will train and fine-tune large-scale Vision-Language Models to reason about complex video. They will build multi-modal architectures and turn breakthroughs into robust APIs and SDKs.

What you will do

• Train and evaluate VLMs specialized for motion understanding in autonomous-driving and robotics datasets.
• Design and scale GPU-accelerated pipelines for training, fine-tuning, and inference on multi-modal data.
• Build agentic evaluation frameworks that benchmark spatiotemporal reasoning, localization accuracy, and narrative consistency.
• Develop and productionize curation loops that use models to generate and refine datasets.
• Publish high-impact research while shipping features that customers use immediately.

Required qualifications

• Strong proficiency in Python, PyTorch, and large-scale ML workflows.
• Research experience in foundation models, VLMs, or multi-modal learning.
• Ability to iterate quickly and autonomously, running experiments end-to-end.
• Experience training or fine-tuning models on video or sensor data.
• Understanding of retrieval systems, embeddings, and GPU optimization.

Nice to have

• Publications/patents a plus
• Contributions to open-source ML frameworks (e.g., DeepSpeed, Hugging Face)
• Experience with vector databases, distributed training, or ML orchestration systems (e.g., Ray, Kubeflow, MLflow)
• Prior exposure to autonomous-driving or robotics datasets

About the company

NomadicML is building a platform that uses Vision-Language Models to transform raw video footage into structured intelligence. The company was founded by Mustafa Bal and Varun Krishnan.