Job Overview
Location
Redwood City
Job Type
Full-time
Category
Software Engineering
Date Posted
July 16, 2026
Full Job Description
đź“‹ Description
- • Build a safer world with us, one incident at a time.
- • Design, build, and optimize the AI infrastructure that powers Ambient.ai's real-time intelligence platform.
- • Work on the systems required to run state-of-the-art deep learning models across many terabytes of video data in real time.
- • Help build and scale infrastructure for inference, evaluation, and continuous model improvement across computer vision models, large language models, large vision models, and multimodal AI systems.
- • Design, build, and maintain cutting-edge AI infrastructure for real-time computer vision, LLM, LVM, and multimodal inference workloads.
- • Build scalable systems for running state-of-the-art models across large volumes of video and sensor data.
- • Optimize inference performance across latency, throughput, GPU utilization, reliability, and cost.
- • Develop robust evaluation harnesses and benchmarking systems to measure model quality, system performance, regressions, and production readiness.
- • Build infrastructure for continuous model evaluation, experimentation, and deployment.
- • Partner with research scientists to productionize the latest advances in computer vision, LLMs, LVMs, RAG, and multimodal AI.
- • Improve model-serving architecture, including batching, caching, routing, quantization, model parallelism, and hardware utilization.
- • Develop data engines and feedback loops for collecting training data, evaluating model behavior, and continuously improving AI performance.
- • Create reliable observability, monitoring, and debugging tools for production AI systems.
- • Help define best practices for deploying, evaluating, and operating AI systems in real-world enterprise environments.
🎯 Requirements
- • 4+ years of industry experience building infrastructure, distributed systems, machine learning platforms, or production AI systems.
- • BS/MS in Computer Science or a related technical field, or equivalent practical experience.
- • Strong programming background, especially in Python, with solid software engineering fundamentals.
- • Experience designing and building scalable machine learning infrastructure for training, inference, evaluation, and deployment.
- • Hands-on experience running deep learning models in production, ideally including LLMs, LVMs, vision-language models, or multimodal models.
- • Strong understanding of inference optimization techniques, including batching, caching, quantization, parallelism, memory optimization, GPU utilization, and latency reduction.
🏖️ Benefits
- • Comprehensive health + welfare package (Medical, Dental, Vision, Life, EAP, Legal Services, 401k plan).
- • Regular Full-time employees receive stock options for the opportunity to share ownership in the success of our company.
- • Flexible time off to rest and recharge, including Winter Break (time off between Christmas and New Year’s for most roles, depending on customer demand).
- • The latest tech and awesome swag will be delivered to your door.
- • Enjoy a full range of opportunities to connect with your awesome co-workers.
- • We love to hike and are foodies, and love music!
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About Ambient AI Inc.
Ambient AI builds computer-vision software for physical security. Its platform runs on existing cameras, continuously monitoring environments to detect threats such as unauthorized access, weapons, or safety incidents in real time. Using proprietary AI models, it filters out false alarms and sends actionable alerts to security teams. The system integrates with access control and video management systems, providing forensic search and analytics for retail, enterprise, and critical infrastructure. Founded in 2017 and headquartered in San Jose, California, the company serves Fortune 500 customers seeking to reduce reliance on human monitoring and improve incident response.
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