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.

Location: China / Taiwan / Hong Kong / (San Francisco with 75% travel to Asia)
Must be fluent (native) in Mandarin and English

Why I’m hiring this role

Manufacturing at scale is chaotic. Growing fast makes it even harder. I’m looking for someone who can step into that chaos, bring order where it matters, and execute relentlessly.

This role is for a technical leader who leads from the front. Someone who can manage people, yes, but more importantly can do the work, coach others by example, and raise the bar across the team. Process matters, but outcomes matter more.

You will own the technical success of our largest American customers operating factories in China, representing tens of millions in re-occurring revenue. You’ll work directly with me, travel heavily, and play a central role in scaling Overview.ai across Asia.

What you’ll do

• Own successful deployment of Overview.ai systems across Asia, from pilot to full production
• Lead and coach a team of 10+ application engineers across China
• Take ambiguous, fast-moving customer problems and turn them into executed solutions
• Be on factory floors regularly, working hands-on with customers and your team
• Train and coach engineers on fundamentals, not just checklists
• Set technical standards by doing, not delegating
• Partner closely with sales, product, and HQ engineering to win and expand large accounts
• Turn on-the-ground learnings into better deployments, better training, and better product

What you need to be great at

This is a hands-on technical leadership role, not a desk job.

You should be comfortable teaching and coaching others on things like:

• Designing and validating jigs and fixtures
• Optics fundamentals, lenses, lighting, and where to source them
• Deep manufacturing line experience (automotive, electronics, precision manufacturing, etc.)
• Rapid prototyping and problem-solving under real production constraints
• Core computer vision fundamentals and inspection logic
• Debugging real-world systems on noisy, high-speed factory lines

If you’ve been a manufacturing manager, applications lead, or technical owner in a fast-growing environment, that’s a strong plus.

Who this role is for

• Native Mandarin + fluent English is non-negotiable
• Technically strong, but biased toward execution over theory
• High energy, high ownership, and comfortable with heavy travel
• A leader who earns trust by doing the hardest work themselves
• Someone who wants real responsibility, not a title
• Interested in learning directly from the founder while building something meaningful

Why this role is special

• Direct exposure to how major industrial systems are sold, deployed, and scaled
• Massive growth opportunity as Overview.ai expands across Asia
• Real ownership over customers, revenue, and team outcomes
• A chance to help solve one of the hardest problems in manufacturing at global scale

If you want a safe, slow-moving role, this isn’t it.
If you want to build, lead, and execute at speed, let’s talk.

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...