Applied Research Scientist
US$180,000 – US$230,000 / yr base salary
Posted 29 Jul 2025
Advertised as “Senior Applied Research Scientist - Foundation Models”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- Hybrid
- Contract
- Full-time
| Base salary | US$180,000 – US$230,000 / yr |
|---|
Field of studyComputer Science, Electrical Engineering (or related)
Study levelMaster's or higher
Build a safer world with us, one incident at a time.
Ambient.ai is the category creator and leader in Agentic Physical Security. Powered by Ambient Pulsar, the first reasoning Vision-Language Model purpose-built for physical security, our platform seamlessly integrates with existing security cameras and physical access control systems to unify monitoring, access control, threat assessment, response, and investigations through an always-on reasoning layer that augments security operators with superhuman capabilities. The results: 95% fewer false alarms, investigations 20x faster, and 10x faster response.
The momentum speaks for itself: we doubled new ARR in FY26, and have delivered results for world-class customers including Cisco, ServiceNow, SentinelOne, TikTok, Bayer, and MoMA. That kind of momentum creates an environment where great people thrive, and it shows: we recently ranked #71 out of 500 on the Forbes best startup employers list.
Founded in 2017 and backed by Andreessen Horowitz, Y Combinator, and Allegion Ventures, Ambient.ai is on a fast-paced journey to fulfill our mission: prevent every security incident possible.
Ready to learn more? Connect with us on LinkedIn and YouTube
About the role:
Ambient.ai is hiring a Senior Applied Research Scientist to build the next generation of foundation models for computer vision. You will join a team responsible for building multimodal models with state-of-the-art performance on real-world vision benchmarks. In this role, you’ll own full-cycle model development: from pre-training and fine-tuning on image-language data to applying distillation and compression techniques for deployment. This is a hands-on, cross-functional role where your work will directly impact our mission of preventing every security incident possible.
What you'll do:
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Develop & Optimize VLMs: Design and optimize transformer-based vision-language models to understand images, videos, and text, and optimize for real-time inference.
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Pre-training & Fine-tuning: Own the full training pipeline—from pre-training on image-text data to fine-tuning for Ambient.ai’s physical security domain and use cases.
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Model Compression & Optimization: Apply techniques like distillation, quantization, and pruning to reduce model size and latency, enabling efficient edge deployment.