ML Platform Engineer

Position Overview

Afresh is seeking an experienced ML Platform Engineer to join our ML Platform Engineering team. This role is crucial for building and maintaining the foundational infrastructure and tooling that powers Afresh's machine learning and applied science solutions. You will contribute to shared components and services that enable our teams to develop, deploy, and scale robust ML models, including a performant data API, configurable featurization, reliable forecasting systems, highly parallel optimization engines, scalable training pipelines, and deep experimentation capabilities. As Afresh grows, the ML Platform Engineer will ensure our platform can gracefully accommodate predictions and simulations across various time scales and complex data hierarchies.

About the Role

As an ML Platform Engineer, you will be instrumental in elevating Afresh's core ML platform to its next level of performance, reliability, and scalability. You will work on critical infrastructure that directly enables all of Afresh's Machine Learning and Applied Science teams to innovate faster and deliver impact. Your contributions will empower Afresh's product suite, including its flagship Prediction Engine, which powers replenishment decisions for over 15% of all produce sold in the United States.

In your first 3 months, you might:

• Deliver a project that helps generalize model configuration.
• Enable no-code model deploys for various ML solutions.
• Vastly improve integration testing across ML systems.

By the end of your first 6 months, you will have:

• Owned the design and implementation of significant scalability improvements and additions to our ML platform.
• Potentially developed new feature pipelines for the recommendation engine.
• Potentially worked to stand up the first instance of real-time inference at Afresh.

Requirements

• BS in Computer Science or a relevant technical field.
• 4+ years of professional software development experience with a proven track record of shipping high-quality applications and services.
• Experience working collaboratively with machine learning engineers, data scientists, or applied scientists on large-scale software projects involving machine learning models.
• Technical leadership experience and a demonstrated ability to mentor junior engineers.
• Deep expertise in library design, API design, data structures, and algorithms.
• Strong familiarity with Python.

Responsibilities

• Build and maintain foundational infrastructure and tooling for ML and applied science solutions.
• Develop and enhance shared components and services for ML model development, deployment, and scaling.
• Improve the performance, reliability, and scalability of the core ML platform.
• Design and implement new feature pipelines and real-time inference capabilities.
• Collaborate with ML engineers, data scientists, and applied scientists.
• Provide technical leadership and mentorship to junior engineers.

Company Information

About Afresh: Founded in 2017, Afresh is on a mission to eliminate food waste and make fresh food accessible to all. Our AI-powered solution optimizes ordering, forecasting, and store operations for fresh food departments in brick-and-mortar grocers. With our Fresh Operating System, we have helped regional and national grocery retailers place $1.6 billion in produce orders across the US and prevent 34 million pounds of food from going to waste.

Afresh offers a unique opportunity to have a massive social impact at scale by leveraging uncommonly impactful software. We sit 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.

Employment Type

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Location Type

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Salary

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