Senior Machine Learning Engineer

at  Toast

Toast is driven by building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love.
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* (Responsibilities)

• 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*? (Requirements)

• 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 model-based pipelines 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.

• 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