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Staff Computer Vision/AI Engineer at BrightAI Corporation. . Location: Palo Alto, CA. Staff Computer Vision/AI  Engineer. . Bright.AI is a high-growth Physical-AI company transforming how businesses interact with the physical world through intelligent automation. We are building a cutting-edge AI platform that processes visual, spatial, and temporal data across billions of real-world events—from edge devices and mobile sensors to large-scale cloud systems.  . . Our team includes world-class engineers and researchers from companies like Microsoft, Amazon, Tesla, and Meta. We are now hiring a Staff Computer Vision / AI Engineer to help shape the future of real-time visual intelligence and deploy next-generation AI systems at scale. . . This is an incredible opportunity to work on cutting-edge AI systems that are redefining physical infrastructure industries. You will work on applied research and production-level ML/AI systems that power real-time decision-making across devices and services. This role requires deep expertise in computer vision, machine learning, and AI system design, with a strong focus on solving real-world problems. You'll work alongside world-class engineers and product leaders to define, build, and ship state-of-the-art AI features that are embedded into our platform.. .  . . Responsibilities:. . . . Lead the full lifecycle of Computer Vision and ML model development — from data collection and labeling through deployment and monitoring in production environments.. . . . Research and implement deep learning models for computer vision tasks including detection, segmentation, classification, tracking, and real-time inference.. . . . Drive CV projects from prototyping to production, in alignment with product and platform goals.. . . . Collaborate with product, hardware, and cloud teams to design end-to-end intelligent features across the stack.. . . . Architect technically robust, scalable, and reliable AI systems in collaboration with cross-functional teams.. . . . Solve complex physical-world challenges through structured experimentation and performance optimization.. . . . Prioritize and manage multiple initiatives to ensure model performance, reliability, and compliance. . . . . Stay at the forefront of ML/AI and foundational models, integrate key innovations into the product roadmap.. . . . Evaluate emerging AI/ML trends and apply them to enable transformative infrastructure automation solutions.. . . .  . . Required Skills & Expertise:. . . . 7+ years of experience in computer vision and ML, with deep expertise in applied deep learning.. . . . Proven ability to deliver production-grade AI/ML solutions in fast-paced, real-world environments.. . . . Full-stack ML development lifecycle experience: data labeling and curation, model training, evaluation, optimization, and deployment.. . . . Hands-on technical skills with DL frameworks (PyTorch or TensorFlow) and string programming skills in Python (C++ is a plus).. . . . Hands-on experience with CNNs, YOLO, Vision Transformers, model compression, and real-time inference optimization.. . . . Hands-on experience deploying models in cloud platforms (AWS/GCP/Azure) and edge devices using TensorRT, ONNX, or TFLite.. . . . Strong problem solving and analytical skills, with the ability to convert ambiguity into actionable insights.. . . . Excellent team work and collaboration skills; ability to work cross-functionally with software, hardware, and product teams.. . . . Effective communicator, capable of conveying complex technical concepts to both technical and non-technical stakeholders.. . . . Self-motivated, proactive, and thrives in a dynamic, fast-paced environment.. . . .  . . Educational Background:. . . . PhD in Electrical Eng., Computer Science, or a related field with a focus on ML/AI for Computer Vision.. . . . Demonstrated research experience in CV with a strong record of publications and/or patents.. . . . Experience applying vision-based AI to real-time IoT systems or edge intelligence platforms.. . . .  . . Bonus Qualifications:. . . . Applied experience in CV for surveillance, physical-world perception problems, remote sensing, or structural health monitoring.. . . . Proficiency in Linux/Ubuntu environments; scripting and tooling around data and deployment workflows. . . . Familiarity with Agile development practices and tools such JIRA, Git, Confluence.. . . . Experience with embedded systems, Docker containers, or Linux-based deployment pipelines. . . . Prior experience in startup or high-growth environments building zero-to-one AI solutions. .