About Shelf Engine

At Shelf Engine, our mission is to reduce food waste through automation. We harness the power of AI to provide real-time, intelligent forecasting and fully automated ordering to food retailers across the United States. We’re able to drastically reduce the amount of food waste generated while simultaneously maximizing sales and expanding margins for grocers—a triple win for suppliers and retailers, consumers, and the environment.

About the role

Skills: Machine learning, C#, Python, SQL, .NET Core, Angular, PostgreSQL

At Shelf Engine, our mission is to reduce food waste through automation. We harness the power of AI to provide real-time, intelligent forecasting and fully automated ordering to food retailers across the United States. We’re able to drastically reduce the amount of food waste generated while simultaneously maximizing sales and expanding margins for grocers—a triple win for suppliers and retailers, consumers, and the environment.

Shelf Engine is searching for a talented Senior Software Engineer focused on Data Science Enablement to join our team. In this role, you will work on machine learning and data science infrastructure - features for training, tracking, deploying and analyzing the performance of machine learning models for our Data Science system. You’ll work closely across both our Engineering and Data Science teams to build infrastructure improvements to our sophisticated forecasting system with our data system and operational control system. You will enable our Data Science team to operationalize models and forecasting improvements quickly and with confidence, and provide visibility into the execution of the forecasting system to the engineering team and operational team users.. You’ll accomplish this by flexing your skill-set, working across the technology stack and the product process.

This position is based in Seattle, WA or remote.

As a Senior Software Engineer at Shelf Engine, you will:

Write scalable/high-performance code on both the frontend and backend, understanding complex technical areas along the way Build efficient and reusable software that underpins complex Data Science and Machine Learning numeric systems Build features related to model training and tuning, model execution/inference, model tracking and configuration, and model performance analysis Build an observable and reliable system by utilizing current observability tooling and robust and maintainable code. Create software features that are robust, reliable, and user friendly for internal teams, working directly with the internal users Run the full software development lifecycle - problem definition, design, development, testing, demoing, and supporting production use of the features you own Be able to balance immediate business objectives against long-term architectural vision Collaborate with fellow engineers, management, and the product management to prioritize and design work Mentor other members of the team in areas you have experience, whether junior or not!

What we are looking for in a candidate:

You embrace our company principles: make the first move, make better decisions, be furiously curious, commit and deliver, have empathy, invent solutions, be authentic 4+ years of production level engineering experience Experience building machine learning or data science systems that are used in live production systems Experience using modern object-oriented languages, cloud services, and relational databases. Experience with python Strong analytical and quantitative problem solving ability You have a bachelor’s degree or equivalent professional experience You are authorized to work in the U.S. for any employer

Some additional nice to have skills and experience:

Experience with common data systems tools and services such as Airflow, Faktory, FiveTran, Snowflake Experience with C# and ASP.NET Core Experience in distributed systems Experience in the business domains of logistics, warehousing, or the food (grocery, etc.) industry Experience with Kubernetes Experience with SQL Server, Postgres, ingestion/ETL, or data engineering Experience with Azure

What Shelf Engine offers you:

A unique opportunity to join a sustainability startup at a small size, making a meaningful impact on the team as well as the environment An inclusive work environment that emphasizes each team member’s personal and professional growth Competitive salary in the range of $140,000 to $170,000 depending on skills and experience Pre-IPO equity with a four-year vesting schedule PTO that is unlimited and self-managed for full time employees 100% employer-paid premiums for medical, dental, and vision insurance for employees, and 50% covered for eligible dependents Coverage for life insurance, short- and long-term disability, and access to a robust Employee Assistance Program Optional employee contribution of pre-tax dollars to medical and dependent care FSA accounts 401k plan through Guideline to contribute to your financial future Seattle only: Company-paid ORCA transit card

About Us:

At Shelf Engine, you will join a team of driven, passionate, and caring people hungry to make change in an untapped industry. We’re not only solving complex technical problems at scale but also tackling key initiatives with significant environmental impacts. Our team is determined to disrupt a massive industry and leave behind a positive legacy for generations to come.

Shelf Engine is an equal opportunity employer and does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Technology

We're taking on arbitrage risk for perishable goods. We do daily demand forecasting based on a number of factors, including historical information, product margins, etc. We have an operationally sophisticated product for automatically managing, dispatching and recording orders, and tracking sales and waste information. Domain areas range from ML and statistical forecasting, to full stack web services and mobile apps. For front end we use Angular for desktop and Ionic for mobile. Backend we are running a C# stack, with a SQL storage layer and utilizing CQRS and event sourcing patterns. For forecasting and ML we use R and python.

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