Ambient.ai
Applied Research Scientist - Foundation Models
Ambient.ai, San Francisco, California, United States, 94199
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Applied Research Scientist - Foundation Models
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Ambient.ai
Build a safer world with us, one incident at a time. Ambient.ai is a unified, AI‑powered physical security platform helping the world’s leading enterprises reduce risk, improve operational efficiency, and gain critical insights. Seven of the top 10 U.S. technology companies, along with multiple Fortune 500 organizations, rely on Ambient.ai to modernize their physical security infrastructure.
Our platform uses advanced AI and computer vision to seamlessly integrate with existing camera and sensor systems, enabling real‑time monitoring and proactive threat detection. By reducing false alarms by over 95%, Ambient.ai allows security teams to focus on real threats and prevent incidents before they occur. Founded in 2017 and backed by Andreessen Horowitz, Y Combinator, and Allegion Ventures, Ambient.ai is a Series B company on a mission to make every security incident preventable.
About the Role Ambient.ai is hiring an 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
Develop & optimize vision‑language models: design and optimize transformer‑based models to understand images, videos, and text, and optimize for real‑time inference.
Pre‑train and fine‑tune: 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.
Apply model compression and optimization techniques: use distillation, quantization, and pruning to reduce model size and latency, enabling efficient edge deployment.
Leverage open‑source and innovate: use and extend state‑of‑the‑art open‑source models, prototype new architectures and training methods to advance Ambient.ai’s multimodal AI research.
Collaborate across teams: work with engineering and product teams to integrate models into the platform, iterating based on real‑world feedback and deployment data.
Engage in research and experimentation: stay current with vision, NLP, and multimodal AI research, designing experiments to test new algorithms and continually enhance core AI systems.
What You’ll Bring
Ph.D. or Master’s in CS, EE, or related field, with a strong foundation in AI/ML (Ph.D. preferred or Master’s with strong experience).
Proficiency in Python/C++ and deep learning frameworks such as PyTorch or TensorFlow, with experience building large‑scale training pipelines.
Hands‑on experience with CNNs, Transformers, and Vision Transformers (ViT). Strong understanding of vision‑language models and how to fine‑tune or adapt them.
Proven skills in model training and optimization, including fine‑tuning on large datasets and applying distillation, quantization, or similar techniques; experience with foundation or multimodal models is a plus.
Strong problem‑solving ability: rapid prototyping, diagnosing failure cases, and iterating on solutions.
Startup experience preferred: comfort with ambiguity, fast iteration, and owning projects end‑to‑end.
Salary and Equity The starting base salary range for this role in Redwood City is $180,000 – $230,000. Base salary is one part of our total rewards package, which includes stock options and the opportunity to share in the company’s growth.
Why Join Us
We are creating an entirely new category within a $120 billion+ physical security industry and looking for team members who are passionate about our mission to prevent every security incident possible.
We have an impressive customer roster of Fortune 500 companies, including Adobe, SentinelOne, and TikTok.
Full‑time employees receive stock options for ownership in our company’s success.
Comprehensive health and welfare package: medical, dental, vision, life, EAP, legal services, and a 401(k) plan.
Flexible time off, including a Winter Break between Christmas and New Year’s.
Access to cutting‑edge equipment, branded gear, and a vibrant team culture.
Opportunities to connect with colleagues across the company.
Ambient.ai is proud to be an Equal Opportunity Employer. Ambient does not unlawfully discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. Ambient is an E‑Verify participant.
Seniority level: Entry level.
Employment type: Full‑time.
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Applied Research Scientist - Foundation Models
role at
Ambient.ai
Build a safer world with us, one incident at a time. Ambient.ai is a unified, AI‑powered physical security platform helping the world’s leading enterprises reduce risk, improve operational efficiency, and gain critical insights. Seven of the top 10 U.S. technology companies, along with multiple Fortune 500 organizations, rely on Ambient.ai to modernize their physical security infrastructure.
Our platform uses advanced AI and computer vision to seamlessly integrate with existing camera and sensor systems, enabling real‑time monitoring and proactive threat detection. By reducing false alarms by over 95%, Ambient.ai allows security teams to focus on real threats and prevent incidents before they occur. Founded in 2017 and backed by Andreessen Horowitz, Y Combinator, and Allegion Ventures, Ambient.ai is a Series B company on a mission to make every security incident preventable.
About the Role Ambient.ai is hiring an 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
Develop & optimize vision‑language models: design and optimize transformer‑based models to understand images, videos, and text, and optimize for real‑time inference.
Pre‑train and fine‑tune: 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.
Apply model compression and optimization techniques: use distillation, quantization, and pruning to reduce model size and latency, enabling efficient edge deployment.
Leverage open‑source and innovate: use and extend state‑of‑the‑art open‑source models, prototype new architectures and training methods to advance Ambient.ai’s multimodal AI research.
Collaborate across teams: work with engineering and product teams to integrate models into the platform, iterating based on real‑world feedback and deployment data.
Engage in research and experimentation: stay current with vision, NLP, and multimodal AI research, designing experiments to test new algorithms and continually enhance core AI systems.
What You’ll Bring
Ph.D. or Master’s in CS, EE, or related field, with a strong foundation in AI/ML (Ph.D. preferred or Master’s with strong experience).
Proficiency in Python/C++ and deep learning frameworks such as PyTorch or TensorFlow, with experience building large‑scale training pipelines.
Hands‑on experience with CNNs, Transformers, and Vision Transformers (ViT). Strong understanding of vision‑language models and how to fine‑tune or adapt them.
Proven skills in model training and optimization, including fine‑tuning on large datasets and applying distillation, quantization, or similar techniques; experience with foundation or multimodal models is a plus.
Strong problem‑solving ability: rapid prototyping, diagnosing failure cases, and iterating on solutions.
Startup experience preferred: comfort with ambiguity, fast iteration, and owning projects end‑to‑end.
Salary and Equity The starting base salary range for this role in Redwood City is $180,000 – $230,000. Base salary is one part of our total rewards package, which includes stock options and the opportunity to share in the company’s growth.
Why Join Us
We are creating an entirely new category within a $120 billion+ physical security industry and looking for team members who are passionate about our mission to prevent every security incident possible.
We have an impressive customer roster of Fortune 500 companies, including Adobe, SentinelOne, and TikTok.
Full‑time employees receive stock options for ownership in our company’s success.
Comprehensive health and welfare package: medical, dental, vision, life, EAP, legal services, and a 401(k) plan.
Flexible time off, including a Winter Break between Christmas and New Year’s.
Access to cutting‑edge equipment, branded gear, and a vibrant team culture.
Opportunities to connect with colleagues across the company.
Ambient.ai is proud to be an Equal Opportunity Employer. Ambient does not unlawfully discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. Ambient is an E‑Verify participant.
Seniority level: Entry level.
Employment type: Full‑time.
#J-18808-Ljbffr