About the Company
Why We Built Lyric: Supply chains are more critical and complex than ever. Every day, large enterprises navigate trillions of possible decisions that could impact the bottom line. Powerful algorithms and AI can address these problems, yet most organizations struggle to leverage supply chain AI at scale. The current SCM technologies are either rigid, limited-scope point solutions or custom solutions built in-house, which demand immense expertise and investment.
That is…until now.
Enter Lyric: Lyric is an enterprise AI platform built specifically for supply chains, offering the best of both worlds:
Out-of-the-box AI solutions for optimizing networks, allocating inventory, scheduling routes, planning fulfillment capacity, promising orders, propagating demand, building predictions, analyzing scenarios, and more, plus
A platform-first approach that empowers both business and technical users with end-to-end product composability, leveraging no-code tools, their own code, or even forking our code to build and refine supply chain decision intelligence
With Lyric, enterprises no longer have to choose between flexibility and speed, they get both.
The Mission: We’re building a new era in supply chain with the team best equipped to lead it. With over 20 years at the intersection of supply chain and algorithms, we developed a deep conviction that global supply chains needed something like Lyric. Since our inception in December 2021, that conviction has been validated time and time again.
Today, a growing number of Fortune 500 companies, including Smurfit WestRock, Estée Lauder, Coca-Cola, Nike, and more, are innovating on their own terms with Lyric. We can’t wait to see what our customers, both current and future, are empowered to build with us next. Come build with us!
Position Overview:
We’re hiring a Sr ML Engineering to help build Lyric’s Predictions workspace — a no-code interface that lets users build predictive models for supply chain problem solving. You’ll work closely with Lyric’s platform teams to orchestrate end-to-end workflows for supervised learning and time series forecasting solutions to deliver a seamless end user experience.
Key Responsibilities:
Adopt the best practices of software engineering development in an agile environment to build end cutting edge software.
Research and conduct quick proof-of-concept solutions on frameworks and technologies to augment the product stack in whichever way necessary.
Take ownership of the product build and evolution journey and bring a culture of craftsmanship to create the best possible version of the product.
Must-Haves:
Sound background in software engineering fundamentals
Deep familiarity with;
Data engineering including building ETL pipelines
Assembling datasets from different data sources and orchestrating their lifecycle with data persistence layers (SQL and NoSQL DB’s)
Experience with CI/CD pipelines and MLOps tooling
Solid programming background in Python, SQL and REST API service development
