Machine Learning Engineer

🕒 June 4

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MailerLite

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2010

💼 Consulting

📣 Marketing

☁️ SaaS

Consulting • Marketing • SaaS

MailerLite is a user-friendly SaaS platform for email marketing and online presence that helps creators, small businesses, agencies and enterprises grow and engage audiences. It provides drag-and-drop email and newsletter editors (including AI-assisted design), automation workflows, triggered email notifications, and list management tools (including email verification). MailerLite also includes website and blog builders, landing pages, signup forms, an iPad subscriber app for offline collection, paid newsletter subscriptions, digital product sales, appointment booking, e-commerce integrations, and a developer API — all backed by integrations with tools like Stripe, Shopify, WordPress and Zapier and by ISO 27001 / GDPR-compliant security.

📋 Description

• Build and ship predictive models on large-scale behavioral and event data - predicting engagement, finding the best time and audience for each message, scoring list health, and discovering customer segments • Fine-tune LLMs on our own data and outcomes to power a goal-driven assistant that recommends and takes action on a customer's behalf • Design and own the training and inference pipelines behind these models - data prep, training, evaluation, and serving • Build evaluation harnesses that prove a model is genuinely better before it ships - measuring real-world lift, not just offline metrics • Enforce reliable, structured model outputs so predictions and actions can be trusted in production • Collaborate with product and engineering teams who consume your models as shared infrastructure

🎯 Requirements

• 3+ years of experience building and shipping ML models in production (not just prototypes) • Strong applied ML fundamentals: feature engineering, calibration, leakage avoidance, and honest evaluation - especially on imbalanced and time-series problems • Hands-on LLM fine-tuning experience (supervised fine-tuning at minimum) • Fluency in Python and the modern ML stack (e.g. scikit-learn, gradient boosting, pandas/Polars, PyTorch) • Comfort writing performant SQL over large datasets and working with event/columnar stores and relational databases • Experience designing training and inference pipelines and the orchestration around them • A strong sense of ownership and the ability to work autonomously in a remote, async team • Clear written communication • At least 4 hours overlap required with CET time zone

🏖️ Benefits

• You'll build ML that actually ships to customers • You’ll have stability • You’ll take ownership • You’ll have experts on hand • You'll pick where you work, every day • You'll grow, develop and evolve