Build a better future. Join us in transforming human and environmental health by reducing food waste and making fresh, nutritious food accessible to all.
Afresh is a revolutionary new approach to fresh ordering, forecasting, and store operations for grocery retailers. Using cutting-edge technology (AI, ML, deep reinforcement learning, etc.), we build tools that help grocers and other supply chain constituents reduce food waste and maximize profit by forecasting demand and optimizing decisions.
Engineering Manager - Full Stack East Bay, CA, United States, San Francisco, CA, United States, or Silicon Valley, CA, United States
Engineering Manager - ML/Data Platform East Bay, CA, United States, San Francisco, CA, United States, or Silicon Valley, CA, United States
Front End Web Developer Austin, TX, United States, East Bay, CA, United States, San Francisco, CA, United States, or Silicon Valley, CA, United States
Full-Stack Engineer Austin, TX, United States or San Francisco, CA, United States
Head of Machine Learning East Bay, CA, United States, San Francisco, CA, United States, or Silicon Valley, CA, United States
Why join us?
We are the rare start-up that actually combines:
Cutting-edge technology - we combine novel ML techniques with empathetic user design to create a truly innovative system.
Tangible, positive social impact - across our customers, our system has decreased food waste by >25%.
High-growth potential - we went from Seed to Series A and signed grocery chains that represent 2500+ stores and 50B+ revenue all in less than 1 year!
We have awesome investors! Our Seed stage investor, Steve Anderson at Baseline, was an early investor at Instagram, Heroku, SoFi, and Stitch Fix, and has been consistently been at the very top of the Forbes Midas List. Our Series A investors are industry veterans such as James McCann, former CEO of Ahold USA, a top grocery retailer.
Food waste is a horrible, environmental blight: about 30-40% of food produced worldwide is thrown away, causing nearly a trillion dollars of economic losses, trillions of gallons of wasted water, and billions of tons of greenhouse gas emissions. In the US, about 40% of all food waste occurs at the retail level and downstream, largely driven by insufficient technology and manual processes. We are actively and tangibly helping solve this problem.
Our technology doesn’t just reduce food-waste — it makes the fresh food supply chain more efficient making fresh food fresher, tastier, cheaper, and more widely available!
You'd be joining an incredible team at the inflection point of serious growth. Everyone at Afresh lives our values - proactivity, candor, kindness, and empathy; and we fully believe that we will have a serious impact on climate change and the world around us.
Engineering at Afresh Technologies
We are a flat engineering organization consists of people working on machine learning, data science/engineering, backend/infrastructure, full-stack web/mobile development, and design. We operate a lightweight Scrum process with two-week sprints and daily standups. We develop our code on Github following the Gitflow model and continuous integration and deployment powered by CircleCI.
We're building a decision-making system powered by reinforcement learning that optimizes tens of thousands of daily ordering decisions in hundreds to thousands of supermarkets across the US. This requires infrastructure that scales state-of-the-art model-based planning algorithms to datasets of tens of millions of data points that are ingested daily. The resulting decisions are communicated to tech-averse end-users via a mobile app. It's an real-life end-to-end problem that has never been solved in the world of fresh food and grocery!
Use state-of-the-art model-based reinforcement learning algorithms to automate tens of thousands of daily ordering decisions in hundreds to thousands of supermarkets across the US. Use supervised learning to create a world model, and apply planning algorithms to determine optimal decisions in that model.
Scale state-of-the-art model-based planning algorithms to datasets of tens of millions of data points that are ingested daily. Develop data pipelines powered by Apache Spark that process and clean data feeds coming from the customers and place them in our data lake.
Take the output from our reinforcement learning model and feed it into a mobile frontend that will be used every day by hundreds of store operators to plan their decisions. These generally tech-averse end-users require a UX that will fit their needs and will make them maximally effective and improve the adherence to our recommendations.
Working at Afresh Technologies
Our four cultural values are: Humility, Proactivity, Humility and Kindness.
We have specific OKR's and strategies to ensure that our top of funnel is diverse, and as a 35+ person company we are actively focusing on implementing processes now to ensure that our company is diverse, equitable and inclusive as we grow!
As part of our commitment to an inclusive workplace, we are happy to offer prospective engineers the chance to connect with our engineering employees who come from underrepresented backgrounds. It’s a way to get a better sense of our team and what it might be like to work with us.
If you’re interested in connecting with our team, be sure to bring this up during one of our introductory calls!
Unmonitored vacation policy.
Prioritizes diversity in hiring
Social impact driven
Work from Home
Interested in this company?
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