Engineering Manager - Machine Learning

Afresh is on a mission to reduce food waste and increase access to nutritious food globally by transforming the fresh food supply chain. Our AI-powered solutions optimize the multi-trillion-dollar grocery industry's food ordering, production, and merchandising processes. We built the first platform capable of handling all of Fresh food’s complexities. We are relentlessly focused on helping grocers reduce waste, increase profitability, and bring better, fresher food to their communities. Afresh is currently deployed in hundreds of grocery stores across the United States and is on track to reduce 30 million pounds of food waste per year with our existing customers alone. By 2021, we're aiming to reduce food waste by a quarter billion pounds per year. We are a passionate team united by our mission to make an impact. As an Afresh employee, you’ll own meaningful work that will challenge you and change the future of how fresh, nutritious food makes its way through the supply chain. We hope you’ll join us!

What will you do?

• Directly impact our mission of reducing fresh food waste by working on our backend data and machine learning platform that uses massive amounts of grocery store data to make ordering recommendations
• Build out our backend data and machine learning platform as well as supporting tooling to process tens of billions of historical data points collected from tens of thousands of retail stores and beyond
• Leverage modern data analysis and processing frameworks, programming languages, and tooling—including Apache Spark, Pandas, Python, and SQL—to provide powerful compute capabilities to our data and ML backend platform
• Scale our data backends that leverage a combination of traditional databases, data warehouses, and data lakes to support varying access patterns
• Scale up your impact by leading technical projects, participating in technical and design decisions, mentoring engineers, and participating in recruiting functions
• Act as an exemplar for our culture of excellence, curiosity, collaboration, proactivity, candor, humility, and kindness

What skills and experience do you need?

• 4+ years of professional software engineering experience
• Outstanding programming skills with deep knowledge of databases, distributed systems, and backend concepts
• Demonstrated ability to design, build, deploy, and manage large production compute or data backend platforms at scale. Experience using modern big data frameworks, scaling computation to hundreds of machines, and/or working with machine learning systems preferred
• Demonstrated ability to triage and solve open-ended, ambiguous systems-level problems
• Bachelors degree in a STEM field, ideally in computer science or related field

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

Founded in 2017, Afresh is the first A.I.-powered fresh food optimization platform for grocery chains. We have partnered with several large grocers representing hundreds of stores and >$10B in revenue. Our cutting-edge AI research has been published in top journals (e.g., ICML). We’re backed by some of the top investors in grocery and tech including Innovation Endeavors (former Google CEO Eric Schmidt’s firm), Baseline Ventures (first money in Stitch Fix, SoFi, Heroku, Instagram), Food Retail Ventures, Maersk Growth, and Impact Engine.

We are building a vibrant, diverse, and inclusive team that embodies our company’s values: proactivity, kindness, candor, and humility. We aspire to continually grow as individuals and as an organization to live these values and realize our mission. We earnestly believe that Afresh represents a one-of-a-kind opportunity to have massive social impact at scale by employing novel technology—and to have a ton of fun along the way.

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