We use technology to make freight more efficient, reducing shippers' costs, increasing carriers' earnings, and eliminating carbon emissions from our planet.
Machine learning is core to Convoy’s mission to automate the logistics industry. Today, we use machine learning to figure out freight prices, shipment relevance for carriers, auction bidding strategy, and other internal processes. We’re looking for a backend engineer who understands how to train and serve ML models in a production environment. You would work with a tight knit group of engineers and data scientists on things like helping us launch new iterations of our recommendation engine, brainstorm improvements to our candidate generation and ranking processes in order to better meet our business needs, and acting as a liaison between our product focused pod and Convoy’s ML platform team, we’d love for you to help us build the infrastructure we need so that data science can independently push changes to production. If you’re excited about ML, are interested in solving business problems, and love building customer facing products, we’d love to chat!
You will:
Make sure that our product team is connected with and aligned to the work that our ML Platform team is doing
Help Data Science launch new models to better predict what offers are relevant to carriers
Build out infrastructure for Data Science to “self-serve” new deployments to production
Find new innovative ways to improve our offer pipeline and apply machine learning to improve business metrics
We're looking for someone who has:
Understanding of fundamental machine learning techniques
5 years+ professional experience successfully applying machine learning to product/business problems
General backend software engineering skills
Experience writing and deploying production code
Experience building and working with data pipelines
Experience communicating with non-technical stakeholdersPython/R/Javascript (Node.js) experience a plus
This job is no longer open
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