Staff ML Platform Engineer, Afresh Technologies
$186-225k
Salary band in Canada is $163,000 - $200,000 CAD
SaaS for grocery store operations
Be an early applicant
SaaS for grocery store operations
101-200 employees
Be an early applicant
$186-225k
Salary band in Canada is $163,000 - $200,000 CAD
101-200 employees
Company mission
To eliminate food waste and make fresh food accessible to all.
Role
Who you are
- BS in Computer Science or a relevant technical field
- 7+ 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
- 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
What the job involves
- 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 performance, reliability, and scalability. You'll work on the 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 our product suite, including our flagship Prediction Engine, to power replenishment decisions on more than 15% of all produce sold in the United States
- In your first 3 months, you might deliver a project that helps generalize model configuration, enables no-code model deploys for our various ML solutions, or vastly improves integration testing across our 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. This might include new feature pipelines that power our recommendation engine, or work to stand up the first instance of real-time inference at Afresh
- Tech Stack: Our backend is pure Python (NumPy, Pandas, Torch, PySpark, Cython, orchestrated in Airflow). We use Databricks as our data warehouse. While we'd like you to have very good familiarity with Python, many of our problems are stack-agnostic
Our take
Antiquated inventory management systems are detrimental to grocers' money and time. Generalized and paper-based systems result in the over-purchase of stock, and this results in waste of fresh food and financial budgets.
Afresh has created an operating system designed specifically to manage inventory and sales of fresh food. The system is powered by AI to help provide forecasting and analysis of inventories, helping grocers stock more economically and thus waste less fresh food.
The company has grown rapidly in recent years, and has partnered with thousands of stores in 40 states across the US. Clients include Albertsons, WinCo Foods, Heinen's, Save Mart, Bashas and Cub Foods.
Freddie
Company Specialist at Welcome to the Jungle
Insights
6% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Aug 2022
$115m
SERIES B
Nov 2020
$13m
SERIES A
Total funding: $147.8m
Company benefits
- Comprehensive health plans
- Generous parental leave
- Equity packages
- 401k matching
- Flexible vacation policy
- Monthly grocery stipend
- Professional development program
- Monthly physical / mental health stipend
- Work from home stipend
Company HQ
Yerba Buena, San Francisco, CA
Leadership
Matt Schwartz
(Co-Founder & CEO)Worked as a consultant for Bain before going on to pursue their passion for food systems. They also previously founded Statfoods.
Volodymyr Kuleshov
(Co-Founder & Advisor)Has a PhD in computer science from Stanford. Alongside Afresh, they are an Assistant Professor in the technology department at Cornell.
Nathan Fenner
(Co-Founder)Has a Bachelors, Masters and MBA from Stanford University. Post studying, they became a Lecturer at Stanford in the Mechanical Engineering department before working at Liquid Robotics.
Share this job
View 4 more jobs at Afresh Technologies