Full Stack Engineer for Machine Learning Products
- Silicon Valley, CA, United States
- $90k - $150k
- 0.05% - 0.25%
You’ll be working onsite at our Palo Alto office, located near the Stanford campus and Caltrain.
What you’ll be doing
- Design and develop features for a computer vision platform that is truly first of its kind
- Identify new technologies and best practices for our growing engineering team
- Improve site performance on both the client and server side
- Incorporate user feedback to design and build a better product
- Create better visualizations for the outputs of computer vision models running on video streams and images
- Ensure that our platform features work at an ever growing scale
How you’ll be doing it
- You’ll be part of a world-class, multidisciplinary engineering team, where each member identifies and prioritizes valuable and interesting new features to work on.
- You will operate in a collaborative but highly autonomous environment that isn’t bogged down by unnecessary meetings or project management.
- You will know that almost everything you build affects real world users, and you will set the quality standards for your work appropriately.
- You will think creatively and your suggestions about new features and ideas we’ll be considered by other members of the team.
- You will have direct access to customers and be able to iterate on your features based on their feedback.
- You’ll be working with modern technologies like React, Node.js, MongoDB, Docker, and Kubernetes.
- You will learn a lot along the way, diving into new technologies and the world of computer vision both on your own and during frequent company tech talks.
What you’ll bring to the table
- You are a self starter who can prioritize what to work on and fully design, build, and write tests for new features.
- You’re comfortable moving across the stack: on a typical day you might optimize a database query and tweak a user interface to be more intuitive.
- You have an eye for design and an understanding for what can make a user interface more intuitive and delightful.
- You can show that you’re smart, analytical, and a fast learner. Sometimes you’ll work on things using unfamiliar languages or technologies, but you know you can handle that.
- There aren’t any strict requirements for your background, but you’re technical. Maybe you have a CS (or similar) degree, or you’re a bootcamp grad with a STEM background and strong portfolio, or you might be self taught with a few years of industry experience.
- It’s a plus if you have experience in areas that might be relevant to a startup working on computer vision: streaming video, data visualization, scaling web applications, DevOps, etc…
What we offer in return
- Competitive pay and equity
- The chance to constantly work on stimulating intellectual challenges
- Gym membership reimbursement
- Free, lunch, snacks, and caffeine every day
- Medical, dental, and vision insurance with 100% coverage
- A flexible schedule that leaves time for all of your other interests
- A budget for whatever hardware will make you most effective
- Resources to learn about the cutting edge of software engineering and computer vision
About Matroid, Inc.
With the rapid growth of artificial intelligence, more and more expert knowledge is required to use cutting edge AI techniques to solve real world problems.
At Matroid, we're building an intuitive product that allows anyone to train and deploy computer vision models without needing to know how to write a line of code. Founded by a Stanford professor in 2015, Matroid has raised $13.5 million in funding, and the product has been used in a variety of security and media applications.
The Matroid engineering culture emphasizes autonomy and rigorous quality. Matroid engineers have ownership of product areas, and are empowered to prioritize, design, and implement features in those areas. Engineers also have latitude in choosing the technologies best suited to meeting our product goals. We also encourage curiosity and learning about new technologies and parts of the stack you haven't worked on before.
Outside of work, we have frequent team outings, cookouts, and retreats, as well as weekly board games.
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