ML Engineer – Vision-Language for Motion & Autonomy

Nomadic AI; San Francisco (CA); On-site; USD 170,000 - 250,000; Full time

Job summary

NomadicML, based in San Francisco, seeks a Machine Learning Engineer to advance motion understanding with vision‑language models and production‑grade ML pipelines. You will train, evaluate, and deploy multi‑modal systems that reason about complex video events and interactions across large datasets.

You will collaborate with founders to scale GPU‑accelerated workflows, build robust APIs, and publish research while delivering customer‑facing features.

Qualifications

• Proficiency in Python, PyTorch, and large‑scale ML workflows.
• Research experience in foundation models, VLMs, or multi‑modal learning (publications/patents a plus).
• 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.

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 (video + language + sensor metadata).
• Build agentic evaluation frameworks that benchmark spatiotemporal reasoning, localization accuracy, and narrative consistency.
• Develop and productionize curation loops that use our own models to generate and refine datasets (“AI training AI”).
• Publish high‑impact research (e.g., NeurIPS, CVPR) while shipping features that customers use immediately.

Skills

Python

PyTorch

large‑scale ML workflows

foundation models

VLMs / multi‑modal learning

video data

embeddings / retrieval

GPU optimization

experimental iteration

Tools

DeepSpeed

Hugging Face

Ray / Kubeflow / MLflow

Job description

NomadicML, based in San Francisco, seeks a Machine Learning Engineer to advance motion understanding with vision‑language models and production‑grade ML pipelines. You will train, evaluate, and deploy multi‑modal systems that reason about complex video events and interactions across large datasets.

You will collaborate with founders to scale GPU‑accelerated workflows, build robust APIs, and publish research while delivering customer‑facing features.