Afresh
AI platform for grocery
SoftwareEngineer,MLPlatform
Neural analysis suggests this role is
optimal for Mid candidates.
“Software Engineer, ML Platform at Afresh. Skills: ML Platform Engineering, Python, AI, Machine Learning. building and maintaining the foundational infrastructure and tooling that powers all of our machine learning and applied science solutions. provide the shared components and services that enable our teams to develop, deploy, and scale robust ML models”
What You'll Achieve.
drive smarter decisions across their entire enterprise; prevented over 200 million pounds of food waste last year alone; work directly translates into massive scale and social good; defines how the world eats; elevating our core ML platform to its next level of performance, reliability, and scalability; innovate faster and deliver impact; power replenishment decisions on more than 15% of all produce sold in the United States; minimize waste and maximize sales
Industry & Context.
tackling the most complex problem in the industry: fresh; drive smarter decisions across their entire enterprise; gracefully accommodating predictions and simulations across various time scales (hours, days, weeks), complex data hierarchies (pallets on a truck, shelves of mangos in a store, chunks of fruit in a bowl), and endless configuration possibilities (average shelf fullness, backroom loads, truck capacities)
This position is not eligible for company sponsorship.
What They're Looking For.
Must Have
BS in Computer Science or a relevant technical field, 3+ 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, Deep expertise in library design, API design, data structures, and algorithms, familiarity with Python
Nice to Have
very good familiarity with Python, genuine curiosity about ML modeling (e. g. , demand forecasting, state estimation, ordering policy), understanding of how scientists work and build tools that bridge the gap between a research notebook and production-grade software
What You'll Do.
building and maintaining the foundational infrastructure and tooling that powers all of our machine learning and applied science solutions
provide the shared components and services that enable our teams to develop
and scale robust ML models
configurable featurization
reliable forecasting systems
highly parallel optimization engines
scalable training pipelines
deep experimentation capabilities
elevating our core ML platform to its next level of performance
work on the critical infrastructure that directly enables all of Afresh's Machine Learning and Applied Science teams to innovate faster and deliver impact
deliver a feature that helps generalize model configuration
enables no-code model deploys for our various ML solutions
vastly improves integration testing across our ML systems
owned the implementation of significant scalability improvements and additions to our ML platform
new feature pipelines that power our recommendation engine
work to stand up the first instance of real-time inference at Afresh
How You'll Work.
Team & Collaboration
Experience working collaboratively with machine learning engineers, data scientists, or applied scientists on large-scale software projects involving machine learning models
Full Job Description
Afresh, the AI platform for grocery, began by tackling the most complex problem in the industry: fresh, and has evolved into the core AI platform for grocers. By leveraging proprietary AI designed for high-volatility environments, we empower partners like Albertsons, Meijer, and Wakefern to drive smarter decisions across their entire enterprise. Following record-breaking 70% revenue growth in 2025, we have scaled to 6 enterprise-grade solutions, with solutions live in over 10% of the U. S. grocery market. Our platform now orchestrates billions of decisions from the store floor to the distribution center and prevented over 200 million pounds of food waste last year alone. If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines how the world eats, there is no better time to join us. The ML Platform Engineering team at Afresh is responsible for building and maintaining the foundational infrastructure and tooling that powers all of our machine learning and applied science solutions. We provide the shared components and services that enable our teams to develop, deploy, and scale robust ML models. This includes a performant data API, configurable featurization, reliable forecasting systems, highly parallel optimization engines, and scalable training pipelines, and deep experimentation capabilities. As our product suite and customer base grow, so does the scale and complexity of what our platform needs to support, gracefully accommodating predictions and simulations across various time scales (hours, days, weeks), complex data hierarchies (pallets on a truck, shelves of mangos in a store, chunks of fruit in a bowl), and endless configuration possibilities (average shelf fullness, backroom loads, truck capacities). About the Role As an ML Platform Engineer on the ML Platform Engineering team, you will be instrumental in elevating our core ML platform to its next level of performan
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