ML Platform Backend Engineer: Scale AI Infra & Models

Lemonade; United States; On-site; USD 120,000 - 190,000; Full time

Job summary

Lemonade is seeking a Backend Engineer to design and scale the Machine Learning Platform powering AI across the business. You’ll join the ML Platform team to build infrastructure that helps data scientists move faster, ship smarter, and operate reliably in production.

You’ll own the end-to-end ML lifecycle, architect cloud-native microservices on Kubernetes, and collaborate across engineering, data science, and product to deliver impactful ML projects. Office-based work pattern expected.

Qualifications

• 3+ years of software engineering experience delivering high-scale, production-grade systems.
• Strong proficiency in Python.
• Experience with relational and NoSQL databases and at least one major cloud platform.
• Experience deploying and monitoring ML models in production.
• Familiar with AI tools and GenAI concepts.
• Bachelor's or Master's in CS/Engineering/Statistics or related field.
• Ready to work in an office environment most days.

Responsibilities

• Design and build the foundational ML platform and AI agents to accelerate data science model delivery across all business units.
• Architect cloud-native microservices running on Kubernetes, using infrastructure-as-code to automate model deployment and management.
• Own the end-to-end ML lifecycle, covering training, testing, deployment, and real-time monitoring.
• Evaluate and choose the right tools and technologies based on workload demands and performance requirements.
• Collaborate with engineering, data science, and product teams to keep ML projects aligned with business goals.
• Identify and fix reliability, scalability, and performance gaps before they become problems.

Skills

Python

Software engineering

Production-grade systems

Education

Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related field

Tools

AWS

Azure

GCP

Kubernetes

Job description

Lemonade is seeking a Backend Engineer to design and scale the Machine Learning Platform powering AI across the business. You’ll join the ML Platform team to build infrastructure that helps data scientists move faster, ship smarter, and operate reliably in production.

You’ll own the end-to-end ML lifecycle, architect cloud-native microservices on Kubernetes, and collaborate across engineering, data science, and product to deliver impactful ML projects. Office-based work pattern expected.