Senior ML Engineer - Email Security
New
J
JobgetherEmail security
Based remotely in MexicoFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English proficiency at B2 level or higher
- Experience
- At least five years of experience delivering detection or classification systems where false positives have meaningful consequences
- Required Skills
- PythonMachine LearningPyTorchGoLinux
Requirements
- At least five years of experience delivering detection or classification systems where false positives have meaningful consequences, such as anti-spam, anti-phishing, anti-malware, fraud prevention, or abuse detection.
- Experience independently taking at least one machine-learning classifier into production, including corpus construction, threshold selection, error analysis, and release decisions.
- Hands-on experience training transformers with PyTorch, including tokenizers, masked-language pre-training, fine-tuning, ONNX export, and CPU inference performance measurement.
- Practical knowledge of Linux, shell scripting, and Python, including work with shared servers and GPU resources.
- Regular use of AI coding agents and development tools.
- English proficiency at B2 level or higher, with strong written communication for technical documentation, specifications, and code reviews.
- Ability to analyze model performance, make evidence-based release decisions, investigate difficult problems, and balance detection effectiveness with false-positive costs.
- Valuable additional experience includes SMTP, MIME, SPF, DKIM, DMARC, and email-filter integrations with Exim, Postfix, or Dovecot.
- Valuable additional experience includes Go or Rust, rspamd or SpamAssassin, large-scale datasets, model optimization, LLM-based annotation tools, and hosting control panels such as cPanel, Plesk, or DirectAdmin.
Responsibilities
- Train, evaluate, and release spam-detection models, including maintaining training corpora, selecting thresholds, analyzing precision and recall, and assessing production readiness.
- Develop production components of a new email-filtering engine in Go, including inference services, mail-filter integrations, tokenization, and streaming message parsing.
- Investigate customer-reported spam and phishing incidents, trace detection failures, and implement fixes through rules, dataset improvements, or model retraining.
- Balance detection rates against false-positive risks to protect legitimate messages while identifying malicious content.
- Maintain corpus-management tools and training infrastructure for experimentation and model releases.
- Review and approve classifier, rule, and model changes to improve quality and support reliable releases.
- Explain classification outcomes and model-scoring behavior to partner engineers and provide technical guidance.
- Write technical specifications, handbooks, merge-request descriptions, and post-mortems.
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