Staff Computer Vision/AI Engineer [Remote]

Staff Computer Vision/AI Engineer We are a high-growth company that is looking for teammates who want to be key contributors to changing the way businesses interact with the physical world through intelligent automation. This is an incredible opportunity to work on cutting-edge AI systems that are disrupting industries. Be a part of scaling a platform that processes real-world visual, spatial, and temporal data from billions of events across edge devices, mobile sensors, and cloud infrastructure. We have the best and brightest minds in AI, Computer Vision, IoT, and Cloud who have built industry-defining technologies at companies like Microsoft, Amazon, Tesla, and Meta. We are looking for an experienced Staff Computer Vision/AI Engineer to join our high-performing team to build next-generation visual intelligence solutions. You will work on applied research and production-level machine learning 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 in scalable and impactful ways. 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 machine learning model development — from data collection and labeling through deployment and monitoring in production environments
• Lead research and implementation of deep learning models for vision tasks such as detection, segmentation, classification, tracking, and real-time inference
• Help in planning and executing AI/ML project phases in alignment with product and platform goals, from prototyping to scalable production rollouts
• Work closely with product, hardware, and cloud teams to design end-to-end intelligent features integrated into devices and applications
• Help in designing and building scalable pipelines for training, evaluating, and deploying models on both cloud and edge platforms
• Develop logical solutions to complex physical-world problems using structured experimentation and performance tuning
• Team with other senior engineers and cross-functional partners to architect technically sound, performant, and reliable AI systems
• Prioritize and manage multiple initiatives, ensuring that all models and systems meet quality, performance, and compliance standards
• Stay current with advancements in Computer Vision ML and AI, particularly in foundational vision models, and bring those innovations into the product roadmap
• Understand the real-world implications of emerging AI/ML trends and apply them to support business transformation through intelligent automation

Skills and Expertise:

• 7+ years of experience in machine learning, with a strong focus on computer vision and applied deep learning
• Proven track record of delivering AI/ML solutions from research to production in fast-paced, real-world environments
• Experience with the full ML development lifecycle — data processing, model training, evaluation, optimization, and deployment
• Deep hands-on technical skills with frameworks such as PyTorch or TensorFlow, and programming expertise in Python (C++ is a plus)
• Deep expertise in convolutional and transformer-based vision models, model compression, and inference optimization
• Experience deploying models in cloud environments (AWS/GCP/Azure) as well as to edge devices (using TensorRT, ONNX, or TFLite)
• Excellent team work and collaboration skills; ability to work cross-functionally across software, hardware, and product teams
• Strong problem-solving skills and the ability to translate ambiguous challenges into measurable solutions
• Ability to communicate complex technical concepts clearly and effectively to both technical and non-technical stakeholders
• Self-driven, proactive, and thrives in a dynamic, startup-like environment

Bonus Criteria:

• Experience applying AI/ML based CV solutions to real-world IoT systems or edge intelligence platforms (e.g., surveillance, monitoring, and anomaly detection)
• Proficiency in Linux/Ubuntu environments; comfort with scripting and tooling around data and deployment workflows
• Familiarity with Agile methodologies and collaborative development tools (JIRA, Git, etc.)
• Background with embedded systems, containers (Docker), or Linux-based deployment pipelines
• Prior experience in startup or high-growth environments, especially building 0-to-1 AI solutions

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