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Lead Machine Learning Developer
Il y a 2 mois
Location: Remote or Flexible
At Proton, we envision a better internet where privacy is a fundamental right. Our mission is to make this vision a reality through innovative technology and user-centric solutions.
Founded in 2014 by a group of scientists from the European Organization for Nuclear Research (CERN), Proton has grown to become a leader in privacy-focused services. Our flagship product, Proton Mail, is the largest encrypted email service globally, and we continue to expand our offerings with Proton VPN, Proton Calendar, Proton Drive, and Proton Pass, empowering users to control their data.
With over 100 million accounts registered across more than 180 countries, our diverse team of over 500 professionals represents more than 40 nationalities. Although headquartered in Geneva, Switzerland, we have a global presence with offices in various cities and a significant number of remote employees.
Role OverviewKey Responsibilities
- Model Development and Integration: Create and implement high-quality user experiences by developing and integrating machine learning models for autofill detection in our password management solutions.
- Process Improvement: Enhance Proton's software development lifecycle by refining our development tools, code structure, and methodologies to streamline ML model training, deployment, and maintenance.
- Code Quality Assurance: Maintain the integrity and sustainability of our codebase by producing clear, well-documented, and testable code, particularly for machine learning functionalities.
- Project Management: Lead the planning, scoping, and execution of new features and technical initiatives, focusing on machine learning capabilities, tailored to your level of expertise.
Qualifications
We welcome candidates with varying levels of experience and expertise. If you possess some of the following skills, we encourage you to apply:
- Frontend Development: Minimum of 2 years of experience with React or similar frameworks, specializing in the creation of efficient and reusable components.
- Quality Standards: Understanding of best practices for maintaining code quality, including continuous integration and deployment.
- User Experience Focus: A commitment to delivering exceptional user experiences, particularly through features enhanced by machine learning.
- Security Knowledge: Awareness of common security vulnerabilities in client-side development and strategies to mitigate them.
- UX and Accessibility: Familiarity with principles of user experience, accessibility, and internationalization.
- DOM API: Experience with or exposure to the Document Object Model API.
- Architectural Design: Ability to translate product requirements into effective architectural designs and implementations.
- TypeScript Skills: Proficiency in TypeScript programming.
- Micro-Frontend Experience: Knowledge of micro-frontend architecture.
Be part of a forward-thinking organization that prioritizes innovation, quality, and a commitment to enhancing user security through advanced machine learning techniques.
