Senior Backend Engineer - ML Platform

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified last checked Jun 13, 2026

Salary

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401(k) match

Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

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Market context

Median wage (BLS OEWS)

$111,944 national median

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Senior Backend Engineer - ML Platform TLV, Tel Aviv, Israel We're looking for a Senior Backend Engineer to help build and scale the Machine Learning Platform that powers how Lemonade uses AI across the business. You'll be part of the ML Platform team, designing the infrastructure that lets our data scientists move faster, ship smarter, and operate with confidence in production. We believe three things matter for every role at Lemonade: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work. Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools. In this role you'll - 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 What you'll need - 6+ years of software engineering experience, with a strong record

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