Senior Software Engineer - ML Platform
Now, more than ever, the Toast team is committed to our customers. We’re taking steps to help restaurants navigate these unprecedented times with technology, resources, and community. Our focus is on building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love. And because our technology is purpose-built for restaurants, by restaurant people, restaurants can trust that we’ll deliver on their needs for today while investing in experiences that will power their restaurant of the future.
Bready* to make a change?
Toast is looking for a machine learning engineer to bring data science capabilities into the Toast platform. You will work with engineers, data scientists and product managers to turn machine learning models into business impact across product lines, including fintech, menu recommendations, ingredient and menu taxonomy, item classifications and customer support through generative AI etc. We need your help to create the infrastructure that enables data scientists to build, release, and monitor models at scale.
About this Roll*: (Responsibilities)
- Apply MLOps expertise internally to help further define and improve the capabilities of Toast’s ML pipelines to increase automation, repeatability, and robustness of our ML practices
- Build ML infrastructure for full model development lifecycle (training, versioning, monitoring, etc)
- Explore and evaluate new ML-related technologies to optimize model performance for latency, availability, and accuracy in collaboration with data scientists and ML engineering team members
- Develop APIs and libraries to deliver machine learning artifacts into production environments
- Help execute on the architectural vision to unlock data science across the entire Toast platform
Do you have the right ingredients*? (Requirements)
- 5+ years of ML software development experience with understanding of the entire ML development lifecycle:
- A proven track record of shipping machine learning solution in production environments
- Deep experience with tools and best practices for developing model deployment pipelines
- Experience with microservice-based architecture, preferably with AWS tooling (SageMaker, DynamoDB, Athena, etc.)
- Strong competency with the following languages (Java/Kotlin, Python), ML frameworks (scikit-learn, Tensorflow, PyTorch) and distributed computing frameworks (Spark, Ray, Dask)
- Experience in software engineering best practices and tools including object-oriented programming, test-driven development, CI/CD, git, shell scripting, task orchestration (Airflow)
- Experience with workflow orchestration tools like Apache Airflow and an open-source infrastructure-as-code tool such as Terraform is a plus
- Foundational knowledge in statistical concepts (e.g. classification, regression, etc) and deep learning algorithms (e.g. CNN, RNN) is desirable
Our Spread of Total Rewards: (Benifits)
- We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.
We are Toasters
Diversity, Equity, and Inclusion is Baked into our Recipe for Success.
At Toast our employees are our secret ingredient. When they are powered to succeed, Toast succeeds.
The restaurant industry is one of the most diverse industries. We embrace and are excited by this diversity, believing that only through authenticity, inclusivity, high standards of respect and trust, and leading with humility will we be able to achieve our goals.
Baking inclusive principles into our company and diversity into our design provides equitable opportunities for all and enhances our ability to be first in class in all aspects of our industry.
Bready* to make a change? Apply today!
Something looks off?