Computer vision engineer at Glimpse

The last decade has been incredibly exciting for electric mobility. However, the electrification of the transportation industry has scaled at the expense of battery quality, leading to uncomfortably high rates of battery pack failure and multi-billion-dollar safety recalls. In our view, every headline of electric vehicles and e-bikes catching fire is a major impediment towards an all-electric future.

This is why Glimpse is on a mission to enable battery quality at scale. 

After having spent a few years in the trenches of battery and electric vehicle factories at Tesla and Toyota, Glimpse’s cofounders developed a vision for a one-stop-shop battery Quality Management Solution, which they actualized through the launch of the Glimpse Portal in March 2024. Today, Glimpse counts some of the world’s largest battery producers and OEMs, such as Lucid Motors and NASA, among its customers.

As an early-stage engineer at Glimpse, you will shape the direction of the company and its product. Working closely with Glimpse's Chief Technology Officer, you will design and build computer vision algorithms that empower Glimpse's customers to quickly diagnose and improve the quality of their batteries. These automated algorithms will unlock key insights into our customers’ terabyte-scale imaging datasets and enable them to regain control over their manufacturing operations. These algorithms will serve as core IP of our product.

You’re fired up by:

• Making electric mobility safer, more affordable, and less wasteful
• Developing robust feature extraction algorithms on terabyte-scale imaging datasets
• Applying the fundamentals of both classical and DL-based computer vision techniques
• Interfacing with customers to develop algorithms that make their lives easier

• Relentlessly getting things done and taking ownership for and pride in your work
• Contributing to our engineering culture and best practices

Our culture and values:

A working draft of our culture and values aspirations can be found here.

Relevant skills: Python image processing stack (numpy, scikit-image, OpenCV, pytorch, and equivalents)

You have:

• Experience with both classical computer vision and deep learning techniques for segmentation, edge detection, and measurement
• Experience writing production-grade image processing pipelines
• Experience with observability, testing, and performance optimization for image processing
• Authorization to work in the US

Nice-to-have:

• Experience with image acquisition and analysis in medical, scientific, or manufacturing environments
• Experience with X-ray imaging datasets
• Experience at high-growth, fast-paced startups

If you don’t meet 100% of the requirements, we still encourage you to apply!

Interview process:

1. Phone screen (30 minutes)
2. Take home test (2 hours)
3. Online technical interview (1 hour)
4. Onsite interview (~½ day)
5. Two reference checks