Top Tech Jobs & Startup Jobs

Lead technical strategy and architecture for AI-powered content systems across the organisation. Define standards for AI evaluation, governance, observability, security, and reliability. Influence roadmaps with senior stakeholders, identify risks and opportunities, mentor senior engineers, and lead complex cross-team initiatives. Combine hands-on delivery of AI/ML production systems with organisation-wide technical direction to ensure scalable, measurable impact on product and learner outcomes.

Reviews Spanish learning content for Dutch-speaking learners across text, audio, and images. Ensures Dutch instructions and translations are natural, Spanish content is accurate, and curriculum progression is effective. Evaluates AI-generated content, documents actionable feedback, identifies recurring issues, and contributes to quality standards and review guidelines while collaborating with linguists, product managers, strategists, and engineers.

Review French learning content across text, audio, and images for accuracy, naturalness, clarity, cultural authenticity, and consistency. Evaluate curriculum structure, progression, and learning goals; quality-check AI-generated content; document actionable feedback; and help develop review guidelines and standards. Collaborate independently with linguists, content strategists, product managers, and engineers to improve the learner experience.

Reviews American English learning content for German-speaking learners across text, audio, and images. Ensures accuracy, naturalness, consistency, cultural appropriateness, and alignment with US English conventions. Evaluates curriculum progression, German translations, and AI-generated content; identifies learner-impacting issues and provides actionable feedback. Contributes to quality guidelines and collaborates with linguists, content strategists, product managers, and engineers.

Reviews British English learning content for German-speaking learners across text, audio, and images. Ensures accuracy, naturalness, UK language conventions, translation quality, curriculum progression, and learner clarity. Evaluates AI-generated content, identifies recurring issues, provides actionable feedback, and helps develop review guidelines and quality standards while collaborating with linguists, content strategists, product managers, and engineers.

Build, operate, and evolve serverless backend services for Babbel Labs’ learning platform using TypeScript, Node.js, and AWS. Own APIs, data contracts, domain models, production reliability, observability, incident response, and safe live-data changes. Collaborate in an agent-first workflow, maintain unfamiliar services, and manage delivery through Terraform and CI/CD. This is a senior individual-contributor role on a small, remote-friendly team.

Support paid advertising campaigns across search, app, social, and display channels. Monitor budgets and performance, build reports, analyze campaign and subscriber data, research competitor advertising, and help test ad copy, creative, landing pages, and audiences. Collaborate with Creative, Analytics, Product, and Martech teams while gaining practical performance marketing experience.

Build and operate an internal developer platform to enable product teams to deploy and run services. Lead cloud migration to a modern, cloud-native AWS setup, design infrastructure and system architecture, implement IaC and delivery pipelines, and collaborate closely with product engineers to unblock them. Use TypeScript/Node and coding agents as part of daily development.

Own the Learning Experience product vision, strategy, roadmap, discovery, experimentation, metrics, and prioritization. Use learner insights, behavioral data, research, and feedback to improve engagement, retention, and learning outcomes. Partner with Engineering, Design, Data, Content, and Product leaders from discovery through launch and iteration. The role also includes delivery-focused initiatives such as platform expansion and subscriber migration.

Own and improve Babbel’s learner-personalization and mastery-tracking systems end to end. Responsibilities include ML research, benchmarking, production deployment, monitoring, incident response, experimentation, and subsystem ownership. The role requires shipping and operating real-time models under user load, evaluating offline and online performance, and using TypeScript or Python with AWS, Terraform, and CI/CD. Experience with probabilistic modeling, Bayesian inference, recommendation or ranking systems, and rigorous A/B testing is required.