Senior Software Engineer, MLE

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 senior Machine Learning Engineer to join the AI team. The ideal candidate has a solid track record in the product-oriented development and deployment of machine learning models. As a Senior Machine Learning Engineer, you will work with a team of machine learning engineers, data scientists and product managers to build machine learning pipelines and deploy models for product lines. 

About this Roll*:

• Work with a team of machine learning engineers and data scientists to develop robust machine learning model pipelines, architect and implement APIs, and create microservices focused on optimizing latency, availability, and overall performance. 
• Implement best practices for version control, code review, testing, and documentation, fostering a culture of high-quality software development
• Stay current with the latest tools, technologies, and best practices in machine learning engineering and cloud-based infrastructure, and drive continuous improvement within the team
• Monitor, troubleshoot, and optimize the performance of machine learning models and related infrastructure
• Embrace agile development methodologies, uphold best practices, and seize ongoing learning opportunities. 
• Engage in collaborative efforts with cross-functional teams, including product managers and engineers, to ensure the delivery of superior quality products.

Do you have the right ingredients*?

• Bachelor's degree in Computer Science, a related technical discipline, or equivalent hands-on experience. 
• A minimum of 4 years of industrial experience in deploying machine learning models.
• Experience with the following languages (Java/Kotlin, Python, Scala) and preferably ML frameworks (scikit-learn, Tensorflow, PyTorch)
• Experience with microservice based architecture, preferably with AWS tooling (SageMaker, DynamoDB, Athena, Glue, etc.)
• Experience in software engineering best practices and tools including object-oriented programming, test-driven development, CI/CD, git, shell scripting, task orchestration
• Profound knowledge of model deployment, orchestration (Apache airflow), scaling, and managing CPU/GPU resources efficiently. 
• Exceptional problem-solving, analytical skills and the ability to tackle complex problems with a critical thinking approach. 
• Outstanding communication and interpersonal skills, coupled with a demonstrated ability to work collaboratively within a team environment.
• Foundational knowledge in statistical concepts (e.g. classification, regression, etc) and deep learning algorithms (e.g. CNN, RNN) is desirable
• Experience with generative AI from concept to production.

Bonus ingredients*:

• Ability to debug and resolve technical issues across the full stack is a plus.
• Experience in developing and building web applications using HTML, CSS, JavaScript and React is a plus.

• Experience in data engineering and programming frameworks such as Spark and Ray is a strong plus.