Level

Proton

Machine Learning Engineer

Proton is hiring a Machine Learning Engineer in Geneva and Taipei. Level rates it ; you can apply on Proton.

Level's read on this job

  • On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include MLOps.
  • Level classifies it as a mid-level role.
  • Level lists 43 other open roles at Proton.

AI in this role

ml-ops

Join Proton and build a better internet where privacy is the default

Proton was founded in 2014 by scientists from CERN on a simple truth: privacy is a fundamental human right. Since then, we’ve built the world’s largest encrypted email service (Proton Mail) and expanded into Proton VPN, Proton Drive, Proton Pass, and Proton Calendar—tools used by millions globally to protect their freedom, fight censorship, and keep their data safe. In some situations, Proton has literally helped save lives!

We are profitable, independent (no VC control), and selectively hire from the top ~1% of applicants. Our 500+ team members across 50+ countries come from leading organizations and elite academic backgrounds. We move fast, keep hierarchy light, and prioritize impact over optics. If you want to do meaningful work with exceptionally high-caliber people, this is it. Join us and do work you can truly be proud of. Check our open-source projects here!

About the role:

The MSA team (Mail Delivery, Spam, and Anti-Abuse) is a multidisciplinary group founded in 2019 to solve complex security challenges across the Proton ecosystem. We build sophisticated systems from scratch that combine human intelligence and machine learning to make tens of millions of real-time or asynchronous decisions daily. Our focus areas include:

  1. Mail delivery and spam prevention

  2. Abuse detection

  3. Account security

  4. Site reliability and resilience

Over the past few years, our custom systems have:

  • Reduced spam filter misclassifications by over 70%

  • Blocked millions of abusive bulk signups

  • Protected hundreds of thousands of users from account compromises

  • Mitigated hundreds of DDoS attacks

Recently, we’ve expanded our impact with Proton Sentinel (an AI-human hybrid security program) and Proton CAPTCHA (our own puzzle system to detect and prevent abuse). We’re now scaling our capabilities with agentic AI to enable autonomous threat detection and response.

In 5 years, we’ve grown from 2 engineers to 40+ engineers and analysts across 3 continents, operating 24/7. We’re looking for curious, collaborative, and impact-driven engineers who thrive in a startup environment and want to shape the future of secure AI.

What You Will Do

  • Design and deploy scalable ML systems using modern MLOps practices, including real-time inference, model monitoring, and automated retraining pipelines.

  • Architect agentic AI systems capable of autonomous threat detection, adaptive policy enforcement, and self-healing security responses.

  • Build tools for model development, debugging, and explainability to accelerate iteration and transparency.

  • Optimize ML workflows for distributed environments to handle large-scale data processing.

  • Collaborate cross-functionally with security analysts, backend/frontend engineers, and customer support to align technical solutions with user needs.

  • Advance the state of ML for anti abuse and account security, exploring cutting-edge techniques like adversarial robustness, graph-based anomaly detection, and privacy-preserving AI.

What You Bring

  • Degree in Computer Science or a related quantitative field, with 2+ years hands-on experience in building and running ML systems.

  • Production-level ML expertise: You’ve shipped models that handle real-world scale and complexity.

  • Hands-on experience with LLMs in agentic environments.

  • Strong software engineering skills: Proficiency in Python, with a solid understanding of backend and server fundamentals.

  • Statistical rigor: Deep understanding of probability, hypothesis testing, and experimental design.

Bonus Points For
  • Experience with adversarial ML or red-teaming ML systems.

  • Experience working on distributed systems.

  • Contributions to open-source security/privacy tools.

  • Knowledge of federated learning, differential privacy, or on-device inference.

  • Familiarity with graph-based anomaly detection or knowledge graphs.

  • Technical leadership: Experience owning projects, mentoring peers, and driving technical direction.

  • Security mindset: Familiarity with abuse patterns, adversarial attacks, or threat intelligence (bonus points!).

Why Join Us?

  • Impact at scale: Your work will protect millions of users globally.

  • Cutting-edge tech: Tackle challenges like agentic AI, real-time threat detection, and privacy-preserving ML.

  • Collaborative culture: Work with a global team of experts in security, ML, and systems engineering.

  • Growth opportunities: Lead initiatives, mentor other, and learn across a diverse technology stack

  • Mission-driven: Contribute to a privacy-first internet where users control their data.

 

What We Offer

  • Work that Matters: millions of people trust Proton with their privacy. We answer only to our users — not advertisers, not investors with conflicting agendas, not governments. The work you do here is real, and the impact is measurable. (read more about our impact here)
  • A great Team: Our team is diverse, collaborative, and tight-knit with people coming from all walks of life, including many of the world’s top academic institutions and organizations, such as MIT, Harvard, Stanford, Caltech, Cambridge, and ETH.
  • Technology: you'll get the right hardware and the right software you need to do your best work.
  • Learning & Development: we invest in your growth because sharp people make us better. Proton is one of the fastest ways to accelerate your career because you'll be thrown into real challenges, with real ownership, from day one.
  • Employee Benefits: your wellbeing isn't an afterthought. We offer strong health coverage, solid retirement options, generous leave, and wellness support so you can bring your best self to work every day
  • Stock Options: at Proton, we all have the opportunity to be owners of the company. From day one, you have a real stake in what we're building. When Proton wins, you win.
  • In-Person Collaboration: Amazing things happen when passionate, smart, and purposeful people get together in the same room. With offices across Geneva, Zürich, Barcelona, London and more, you'll spend most of your time collaborating face-to-face with people who genuinely care about what they're building
  • Food: Lunch and snacks are on us every day in our offices so you can focus on the work and not on what's for lunch.
  • Transport: getting to the office shouldn't cost you. We cover public transport, bike allowances, or parking, whichever works for you.
  • Flexible Working: you own your schedule. Set hours that work for you and your team — because outcomes matter more than when the clock says you started.

 

Our Commitment to Diversity and Inclusion

At Proton, we believe diversity drives innovation and strengthens our mission to provide privacy as a default for all. We are committed to fostering an inclusive environment where all individuals, regardless of race, ethnicity, gender, age, sexual orientation, physical ability, or socio-economic background, feel valued and empowered. We strive to create equal opportunities, promote open dialogue, and support continuous learning to ensure every voice is heard and respected.

If you need any extra support or reasonable adjustments during the hiring process, please let your talent partner know.

 

Candidate Privacy Notice

When you apply for a position, refer a candidate, or are considered for a role at Proton Technologies AG (Proton, we, us, or our), your information is stored in Greenhouse, in accordance with their Service Privacy Policy. This information is used to evaluate your suitability for the posted position. We also retain this information for consideration for future roles that you may apply for or that we believe may align with your background and skills.

If we no longer have a legitimate business need to process your information, we will either delete or anonymize it. Should you have any inquiries about how we use or manage your information, or if you wish to access, correct, or delete your data, please contact our privacy team at careers@proton.ch.

Proton does not accept unsolicited resumes from any sources other than directly from candidates. We will not pay a fee for any placement resulting from an unsolicited offer, even if the candidate is subsequently hired by Proton.

To learn more about our privacy policy, please visit our privacy policy page.

#LI-ONSITE

How we rate this

Machine Learning Engineer at Proton rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML Ops

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$195k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. How would you decide a model or AI system is ready to ship?
  3. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: ML Ops. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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