Member of Technical Staff, Machine Learning - NomadicML
Remote • San Francisco • FullTime
Posted 11mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Machine Learning Engineer
About the job
NomadicML is building a platform to unlock machine intelligence from over 5 trillion miles of driving footage. They are developing Vision-Language Models (VLMs) that transform raw footage into structured intelligence for autonomy and robotics, partnering with industry leaders to extract insights from vast amounts of data. The company was founded by experts in distributed systems, large-scale model training, and AI research.
This role is for a Machine Learning Engineer who will work at the intersection of foundation model research and production engineering. You will be instrumental in training and fine-tuning large-scale VLMs to understand complex real-world video, focusing on building multi-modal architectures that can perceive, localize, and describe motion events. Your work will translate research breakthroughs into robust APIs and SDKs for enterprise customers.
Responsibilities
- 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 to benchmark spatiotemporal reasoning, localization accuracy, and narrative consistency.
- Develop and productionize curation loops for dataset generation and refinement using AI models.
- Publish high-impact research and ship customer-facing features.
Requirements
- 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.