ML (Machine Learning) and Backend Engineer

San Francisco, California, United States expand job description ↓

Description

About MTailor

MTailor sells custom clothing by measuring you with your phone's camera on iOS and Android. MTailor’s computer vision technology is 20% more accurate than a professional tailor. We can deliver your entire wardrobe - jeans, dress shirts, suits, and even t-shirts.

MTailor is the first easy and accessible way to experience the luxury of custom clothing. At the same price as many mainstream off-the-rack clothiers (e.g., J. Crew, Brooks Brothers, Ralph Lauren) and with the convenience of an app, you can get clothing made to fit you perfectly, instead of clothing made to fit someone else.

We're a very full-stack company; we market our own brand direct to consumers, design our own proprietary vision and fit algorithms, and we even own and run our own factory.

About Your Role

Join MTailor and own our fit machine learning algorithms and most of our backend infrastructure. You will apply machine learning to a novel task – fitting physical clothing to customers! You will propose and implement experiments and improvements to our data-driven fit algorithms, which can come from anywhere in our tech stack, from improving the neural net architecture to collecting new / better data to working with our in-house fit expert (our apparel patternmaker). You will also take ownership of our backend infrastructure, which includes ownership for new database features and reports, our measurement generation system, and our garment pattern generation system. You will work with various internal stakeholders, like customer support, factory operations, and our finance analyst, to design and implement software and reporting to make them more effective.

We’re Looking for Someone Who:

  • Is adept at math and statistics
  • Enjoys significant ownership over product and their work
  • Can work independently
  • Thrives in a variety of engineering settings
  • Considers themselves framework agnostic - wants to use the right tool (language / framework / tech stack) for the task at hand
  • Likes to ship code and drive results
  • Enjoys collaborating with non-technical stakeholders

Projects You Would Work On:

  • Investigate various ways to improve our measurement prediction algorithms, such as trying new ML architectures and adding new sources of signal (e.g., iOS depth data). You would end up doing a combination of coding, out-of-the-box thinking, cross-functional collaboration, and mathematical analysis. This project is about improving our core brand promise of a perfect fit.
  • Update and add new features to our customer support tooling, such as integrating stripe for faster refunds. Because everything is made bespoke, we build 1:1 relationships with many of our customers, and our customer support team is the front line of building those relationships.
  • Work with our apparel patternmaker to add new dimensions of fit (new measurements) to our clothing and improve our fit. With new measurements in a garment, we can solve customer fit problems that couldn’t previously be addressed.
  • Analyze usage patterns in our app and purchasing behavior to more effectively guide product decisions and advertising spend.
  • Own our backend systems and extend its capabilities to improve our production capabilities. One small example would be to update our inventory system so that our tuxedo fabric inventory and suit inventory (which share the same underlying fabric) are unified; currently, our system can list our black tux as out-of-stock and our black suits as in-stock, even though we make both of them with the same fabric.

MTailor Company Values

  • Testing and Data - we like to test ambitious hypotheses with the lowest amount of effort
  • The Customer - we always start with what the customer wants (for both new features and product simplifications)
  • An Excellent Work / Life Balance - everyone has a life outside of work (and we encourage that); we are focused on results, not time in the office
  • Self-Motivation - it is frequently up to you to design and execute new initiatives
  • Collaboration and a friendly environment (we hate politics)
  • Building a great, sustainable business
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