Principal Machine Learning Engineer

Toast creates technology to help restaurants and local businesses succeed in a digital world, and they are seeking a hands-on Principal Machine Learning Engineer to join their AI & Strategy Engineering team. The role involves building tools to enhance sales operations through backend engineering and Machine Learning, focusing on developing intelligent workflows that improve decision-making for sales users.

Responsibilities:

• Hands-on Execution: Spend the majority of your time "hands-on-keyboard," architecting and coding high-performance backend services and ML pipelines
• 0-to-1 Development: Build and prototype new internal products from scratch that leverage LLMs and Agentic AI to automate account research, lead prioritization, and complex quoting logic
• Core Intelligence Models: Design and implement ML models that provide real-time recommendations to sales users, reducing manual entry and increasing deal velocity
• Infrastructure Integration: Develop the backend connective tissue between our custom quoting engine, Salesforce, and internal data lakes to ensure a seamless, low-latency end-to-end experience
• Technical Problem Solving: Act as a domain expert to solve complex synchronization and architectural challenges across the GTM stack, ensuring systems are scalable and resilient
• Quality & Mentorship: Drive engineering excellence through rigorous code reviews, automated testing, and by modeling best practices for SE1-SE3 engineers on the team
• Build Great Products: Deliver significant core capabilities that have broad impact; take high-level goals and turn them into sequenced, production-ready code
• Problem Solve: Anticipate shifts in product needs and build flexible, decoupled backend systems that can evolve with our AI strategy
• Deliver Quality: Ensure the reliability of GTM tools by building deep observability into every service you ship

Requirements:

• Extensive experience in backend languages (Java, Go, Python) with a track record of building complex, distributed systems
• Practical, hands-on experience deploying Machine Learning models and building with LLMs (e.g., LangChain, RAG architectures, or Model Fine-tuning) in a production environment
• Experience building or deeply integrating with complex enterprise software, specifically custom quoting engines or CRM internals (Salesforce Apex/LWC)
• Ability to design event-driven architectures and manage data flow across disparate systems with high integrity
• Bachelor's or Master's degree in Computer Science, or a related technical field
• Experience building internal 'Sales Tech' or 'Fintech' tools that directly impact revenue
• Familiarity with AWS data services (SageMaker, Lambda, SQS)
• A passion for removing 'human-in-the-loop' friction through intelligent automation