Machine Learning Engineer, Dashlane

• You will be based in Paris, with a hybrid policy (3 office days / week) and English as your working language
• We come together in the office on Mondays, Tuesdays, and Thursdays, while Wednesdays and Fridays offer more flexibility for focused work
• A Master / Engineer degree in Machine Learning/AI or Computer Science
• 4+ years of professional experience in product led company
• Agile team with industry grade standards for development and software delivery
• Including 2+ years of experience in R&D
• Practical experience in Machine Learning based application
• Handling large amounts of data
• Python, ML frameworks (Scikit-learn XGBoost…) and deep learning frameworks (PyTorch, Hugging Face…)
• Scientific mindset and technical rigour
• Fluent in AI-assisted engineering
• Fluent in English (as the team is international)

Desirable

• You'll work on cutting-edge research in web understanding, using large labelled and unlabelled datasets of web pages
• As a member of the ACE team, you'll help pioneer a state-of-the-art web analysis that will make life easier and more secured for millions of people worldwide
• Its mission is to enhance user security and core product features through intelligent, AI-powered capabilities, such as improving the autofill experience, detecting credential risks, and protecting against phishing attacks
• The team comprises Software Engineers, and Machine Learning Engineers, to ensure the quality of our analysis
• We leverage advanced Machine Learning techniques to build intelligent security tools within a zero-knowledge architecture
• Our blog post demonstrates how we implement autofill capabilities without accessing user data
• We also explain our privacy-preserving approach to real-time threat detection and phishing prevention
• We also advocate for public specifications for field autofill, like Semantically Annotated Web Forms
• Join our team and help us make a difference in the world!
• About our stack:
• Languages:
• Backend: NodeJS, Typescript
• Frontend / internal tooling: React, Typescript
• ML: Python
• ML: Scikit-learn, Optuna, Onnx
• MLOps: Dvc, Mlflow
• Versioning: Gitlab
• CI/CD: Gitlab, Sonarqube, Terraform
• AI : Claude Code
• Work on R&D initiatives around web pages understanding and their applications to a Credential Protection (password manager, identity provider, threat detection)
• Collect data, train model, make hypothesis, experiment and analyse results
• Deploy, evaluate, and continuously improve AI-powered features and agentic systems in production, including LLM-based applications, retrieval augmented generation (RAG), tool-using agents, and workflow automation
• Help maintain and improve our existing data pipelines (data collection tools and databases, model training pipelines, integrations into the Dashlane web extension)
• Work with ML Engineers, Software Engineers, product managers, designers in a highly collaborative environment where everyone shares ownership of the company's success
• Act as an AI Pioneer within the engineering organisation, demonstrating proven experience integrating modern GenAI tooling into day-to-day workflows
• Learn every day, and share your knowledge with your coworkers

• Introductory interviews:
• 1st - Recruitment screening (~30min)
• 2nd - Hiring manager screening (~30min)
• If your background fits the requirements of the position, we start with an introductory call to discover more about you and answer your questions. After this, you'll meet the hiring manager and dig deeper into the responsibilities and challenges of the role. If the hiring manager thinks this is a fit for the role, they will move you to the next stage
• Technical interviews:
• 1st technical stage - Take-home test/deep tech for engineering (1h)
• 2nd technical stage - Problem-solving/technical interview (1h)
• These interviews are the ones where you’ll prove your technical skills. They may include a take-home test, problem-solving questions, or interviews with experienced team members. For engineering roles, you might expect a technical interview about deep tech and a second interview about problem-solving
• Final stages:
• 1 Final interview with the hiring manager (~1h)
• 1 Final interview with Team/VP/Exec (~30min)
• In the final stage, you’ll meet again with the hiring manager and meet the leadership team. While we gather feedback from all the Dashlaners you met, we'll ask you for a few references. If all goes well, we will present you with an offer