Senior Software Engineer, Toast

• The ideal candidate has a solid track record in the product-oriented development and deployment of machine learning models for end-to-end service
• Bachelor's degree in Computer Science, a related technical discipline, or equivalent hands-on experience
• A minimum of 4 years of industrial experience in software development
• Proficiency in Java programming language and knowledge of front-end technologies like HTML, CSS, JavaScript, TypeScript, and frameworks like React or Angular, familiarity with back-end frameworks like Spring or Java EE, experience with databases and SQL, understanding of web services and APIs, and familiarity with cloud platforms and DevOps practices
• Experience with Java/Kotlin and Python
• 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

Desirable

• We are looking for a Senior Software Engineer to join the AI team. As a senior Full Stack 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
• 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
• Engage with technology partners to build, prototype and validate scalable tools/applications end to end (frontend, backend, data)
• 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