Overview is a company that takes the cutting edge in computer vision and deep learning and applies it to previously unsolvable manufacturing inspection problems. We are truly a full stack company. We install physical cameras into the facility, run inference on the edge and manage massive deployments. Overview also streams gigabytes of video/image data to the cloud for our web platform to give customers advanced insights and analytics.

We are looking for engineers who like to solve tough challenges across the stack. This might include wrangling 500mb images or deploying optimized models in one click that can handle 10 parts a second. We are looking for people who are dynamic, who are excited to work on a different challenge every week, whether it's the final inspection on a medical device or making sure a razor blade has a perfect edge.

About Overview

Overview is an AI-powered camera company transforming manufacturing quality and automation. We are a leader in AI for industrial applications, building category-leading AI vision systems trusted by over 150 factories worldwide . Our flagship products, OV20i and OV80i, combine NVIDIA GPU-powered hardware with best-in-class AI models to deliver defect detection that outperforms industry incumbents.

We are seeking a Software Engineering Manager to lead and grow our engineering team, while coordinating closely with teams in Brazil and the US. You will oversee execution of the technical roadmap for current and future products, manage and develop a team of remote and hybrid engineers, and work seamlessly across time zones to deliver world-class industrial AI products. This is a hands-on leadership role with high visibility and significant impact on

Responsibilities

• Roadmap Execution: Work with leadership to prioritize and manage the technical feature roadmap for both current and next-generation AI vision products.

• Team Leadership: Lead, motivate, develop, and manage a team of remote and hybrid engineers, including cross-site collaboration with Brazil and remote-based teams.

• Release & Process Management: Set up and maintain release structures, manage sprints, and track performance to ensure predictable, high-quality deliveries.

• Requirements & Communication: Define requirements, set context and priorities, and report progress to leadership and the engineering organization.

• Cross-Time-Zone Collaboration: Work seamlessly across multiple time zones (Brazil, Taiwan, US West Coast).

• Travel: Periodically travel to support team members and/or work with customers.

• Culture & Performance: Align very bright, high-performing individuals in a fast-paced startup environment, fostering a culture of excellence and ownership.

Why Join Overview

• Lead a key global engineering hub in Taiwan, working directly with teams across APAC, LATAM, and the US.

• Shape products that are transforming manufacturing quality worldwide.

• Competitive compensation, equity, and benefits in a fast-growing AI company.

Requirements

Qualifications

Required:

• 3+ years of experience managing a team of software or firmware engineers at a high growth company.

• 7+ years of work experience in a software company.

• Track record of delivering production software products, ideally in embedded systems, computer vision, or industrial automation.

• Experience in setting up release structures, managing sprints, and measuring engineering performance.

• 2+ years of experience in defining requirements, setting priorities, and reporting progress for leadership and teams.

• Self-starter comfortable working across remote teams, managing ambiguity, and making decisions with incomplete information.

• Strong English communication skills, both written and verbal.

Preferred (Pluses):

• Experience creating processes in a startup or rapid-growth setting.

• Experience working in China and Mandarin proficiency.

Overview's tech is far reaching. We deploy highly reliable camera hardware and GPU's into manufacturing and industrial settings. We have an IoT fleet management stack to update, secure, and manage our fleet of devices. We stream this data to our cloud or to a customers hybrid cloud where we have a user facing platform where customers can interact with their devices, deploy new deep learning models, and see advanced analytics.

We use Docker to deploy web infrastructure and deep learning models. We have an extensive deep learning stack using Tensorflow, PyTorch and packaged with Onnx. Our frontend is in React, which is updated in real time from our fleet using MQTT. And the list goes on...