ML Engineer - Email Security

CloudLinux Inc. develops the Imunify family of security products, designed to protect hosting environments from a wide range of cyber threats. One of these solutions is Imunify Email, an email security product that protects hosting servers against spam, phishing, and other email-based threats.

Imunify Email filters mail on about 5,000 hosting servers. Today the filter is rspamd with rules and a scoring model we train in-house. We are replacing it with a transformer we trained ourselves that runs on the customer's own CPU in under 100 MB and already beats rspamd at every operating point we measured. We are looking for a Senior Machine Learning Engineer to join our team and work alongside the engineer currently responsible for both the existing spam-filtering pipeline and the new ML model. Together, you will drive the development, improvement, and production rollout of our email security technology.

What you will do:

• Train, evaluate, and release spam-detection models: build the corpus, pick the threshold, read the precision/recall report, decide ship or retrain.

• Build the production side of the new engine in Go: the inference service, the mail-filter integration, the tokenizer, the streaming message parser.

• Fix detection quality end to end, from a customer's "this phishing got through" to a rule, a corpus fix, or a retrain, with the false-positive cost weighed against the catch.

• Keep the corpus tooling and training infrastructure running.

• Review and approve classifier, rule, and model changes, so no release waits on one person.

• Answer partner engineers who ask why a message scored the way it did.

• Write specs, handbooks, and post-mortems. That is how this team transfers knowledge.

Your first six months:

• Month 1: you ship a rule-model release on your own.

• Month 3: your first piece of the new engine is merged and running on staging.

• Month 6: a model release goes out while the principal engineer is away.

Requirements

What you bring:

• 5+ years of shipping detection or classification systems where false positives have a cost you had to defend: anti-spam, anti-phishing, anti-malware, fraud, abuse.

• You have taken at least one ML classifier to production yourself: corpus construction, threshold selection, error analysis.

• Hands-on transformer training in PyTorch: tokenizers, masked-language pre-training, fine-tuning, ONNX export, CPU inference measurement.

• Linux, shell, and Python on shared servers and a shared GPU.

• Daily usage of AI coding agents and tools.

• English at upper-Intermediate (B2) level or higher, with particularly strong written communication skills for technical documentation, specifications, and code reviews. Your specs and merge-request descriptions count as much as your code.

It is a strong plus if you have:

• Email internals: SMTP, MIME, transfer encodings, SPF / DKIM / DMARC, how Exim, Postfix, and Dovecot handle mail to a filter.

• Experience in creating embedded models

• Go or Rustfor systems code: parsers, streaming, memory budgets, concurrency.

• rspamd or SpamAssassin internals: rules, composites, Lua plugins, mass-check scoring.

• Multi-million-sample corpora, labelling pipelines, annotator tooling.

• Small models for constrained hardware: quantization, distillation, latency budgets.

• LLM-based labelers or validators for scaling annotation.

• Hosting panels: cPanel, Plesk, DirectAdmin.

Benefits

What's in it for you?

• A focus on professional development.

• Interesting and challenging projects.

• Fully remote work with flexible working hours, that allows you to schedule your day and work from any location worldwide.

• Paid 24 days of vacation per year, 10 days of national holidays, and unlimited sick leaves.

• Compensation for private medical insurance.

• Co-working and gym/sports reimbursement.

• Budget for education.

• The opportunity to receive a reward for the most innovative idea that the company can patent.