Senior Machine Learning Engineer

| San Francisco
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Afresh is on a mission to eliminate food waste and make fresh food accessible to all. Our first A.I.-powered solution optimizes ordering, forecasting, and store operations for fresh food departments in brick-and-mortar grocers. With our Fresh Operating System, regional and national grocery retailers have placed $1.6 billion in produce orders across the US and we've helped our partners prevent 6.9 million pounds of food from going to waste. Working at Afresh represents a one-of-a-kind opportunity to have massive social impact at scale by leveraging uncommonly impactful software – we hope you'll join us!

About the role
The Prediction, Optimization, and Planning (POP) team builds Afresh's core replenishment technology. Our models are directly responsible for ordering millions of dollars of fresh inventory across the world every day; fresh food ordering is an extremely complex high-dimensional decision-making problem! We face the complex challenges presented by decaying product, uncertain shelf lives, varying consumer demand, stochastic arrival times, extreme weather events, and tight performance constraints (to name a few). We tackle these problems with a mix of machine learning, large-scale simulation, and optimization technologies.

 

You will be working on pushing the boundaries of our system's performance on product categories we're already live in, as well as expanding our product to entirely new categories. You will be responsible for implementing new systems end-to-end, including working with product teams to define the business needs of a solution, reviewing research papers and implementing novel ideas, and scaling up experiments to generate predictions and decisions on millions of items every day. Your work will be visible from day one, will make a substantial impact on decreasing food waste, and will lead to fresher, healthier produce for millions of people across the world.

  • In your first 3 months, you will experiment with new features, train and validate new models, and push updates to all of our customers. You will build a strong understanding of perishable inventory control, time series forecasting, and simulation techniques.
  • By the end of your first 6 months, you will have proposed, implemented, and rigorously tested algorithmic or engineering improvements to our core models, featurization, or automatic training and experimentation systems.
  • By the end of your first year, you will have implemented new modeling techniques, expanded our product offering to new categories with novel algorithms, and scaled your solution to our entire customer base.
  • We need to make optimal ordering decisions for millions of items for weeks at a time, and our system must be fault-tolerant to an extreme. Our partners rely on our system to order millions of dollars of inventory every day, and so your code must be rigorously validated, tested, and bug-proof. This is not an analytics team.

Skills and experience
The following represent attributes our ideal candidate possesses. We encourage all highly-qualified candidates to apply, even if they do not fulfill all the listed criteria.

  • 4+ years of professional software development experience with advanced machine learning or statistical and numerical optimization methods.
  • You have repeatedly and successfully taken complex research ideas from experiment to production, and you write high-quality and high-performance code that lives outside of experiments.
  • Familiarity with forecasting techniques, time series analysis, and large-scale stochastic optimization is a plus.
  • A graduate degree in operations research, computer science, electrical engineering, statistics, or similar quantitative field is a plus.

About Afresh
Founded in 2017, Afresh is working on the #1 solution to curb climate change: reducing food waste. By combining human insight and transformative technology, we're helping grocers provide fresher food to customers at more affordable prices.
Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals including ICML, and we've raised over $148 million in funding from investors including former co-CEO of Whole Foods Market Walter Robb and Eric Schmidt's Innovation Endeavors.

Fresh is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility.
Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law.

A qualified candidate must reside in or be willing to relocate to one of these states to be considered: AR, CA, CO, FL, GA, IL, KY, MA, MI, MS, MO, NV, NJ, NY, NC, OR, PA, TX, WA, WI

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Location

We work across the U.S., but call San Francisco home. Our headquarters is in the Financial District.

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