[Remote] Applied Research Scientist - Foundation Models at Ambient.ai

Redwood City, California, United States

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Not SpecifiedCompensation

N/AExperience Level

N/AJob Type

Not SpecifiedVisa

N/AIndustries

Requirements

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)
Proficient in Python/C++ and deep learning frameworks like PyTorch or TensorFlow
Comfortable with 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: quick prototyping, diagnosing failure cases, and iterating on solutions
Startup experience preferred: Comfortable with ambiguity, fast iteration, and owning projects end-to-end

Responsibilities

Develop & Optimize VLMs: Design and optimize transformer-based vision-language models to understand images, videos, and text, and optimize for real-time inference
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
Model Compression & Optimization: Apply techniques like distillation, quantization, and pruning to reduce model size and latency, enabling efficient edge deployment
Leverage Open-Source & 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
Cross-Team Collaboration: Work with engineering and product teams to integrate models into the platform. Iterate based on real-world feedback and deployment data to improve performance
Research and Experimentation: Stay current with vision, NLP, and multimodal AI research. Design experiments to test new algorithms and continually enhance our core AI systems

Skills

Ambient.ai

AI software for proactive physical security

About Ambient.ai

Ambient.ai enhances physical security systems with software that uses artificial intelligence and computer vision. The technology helps security teams shift from reactive to proactive operations by detecting unusual changes in human behavior and locations, without relying on facial recognition. This approach respects privacy while providing AI-verified alerts that reduce false alarms and improve efficiency. The company aims to serve organizations needing security solutions while continuously adapting to the evolving risk landscape.

Palo Alto, CaliforniaHeadquarters

2017Year Founded

$70.2MTotal Funding

LATE_VCCompany Stage

Cybersecurity, AI & Machine LearningIndustries

51-200Employees

Benefits

Healthcare - Medical premiums are covered up to 95% for employees. Dental and Vision is covered at 75%.

401(k) - Choose our pre-tax or Roth 401K plan options, via Guideline, to save for retirement

WFH Stipends - We offer monthly reimbursement for phone and monthly reimbursement for wifi

Time Off - Employees need to recharge their batteries: it improves productivity, creativity and overall job satisfaction! Get your work done, loop in your manager and take a reasonable amount of time off

Employee Resource Group - Join or start one!

Other - Employee Assistance Program and Legal Services

Early Stock Option Exercise

Life Insurance

Visa & Greencard Sponsorship

Risks

Emerging AI security startups increase competition, threatening market share.

Privacy concerns and regulatory scrutiny could impact operations in strict regions.

Dependence on venture capital funding poses financial risks if future rounds falter.

Differentiation

Ambient.ai uses AI to detect behavior changes, not facial recognition, ensuring privacy.

The platform integrates with existing security systems, enhancing proactive threat detection.

Real-time adaptation through threat signatures allows for dynamic response to security risks.

Upsides

Rising demand for AI-driven analytics enhances Ambient.ai's market potential.

Integration with IoT devices offers comprehensive security solutions for clients.

Edge computing adoption accelerates data processing, improving threat detection efficiency.

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