Senior Machine Learning Engineer (Cybersecurity)

TL;DR

Senior Machine Learning Engineer (Data Science/ML): Building and optimizing models and data-driven systems to classify and enrich vast amounts of Internet telemetry with an accent on applied ML workflows and high-quality dataset generation. Focus on designing feature pipelines, model evaluation frameworks, and scalable inference services to make the Internet more explainable.

Location: Remote within the continental United States

Salary: $150,000 - $203,000 + bonus and equity

Company

hirify.global delivers real-time Internet intelligence and actionable threat insights to global governments and Fortune 500 companies by creating a comprehensive map of the Internet.

What you will do

• Build and improve ML models and systems to classify, cluster, label, and enrich Internet-observed assets.
• Design and develop applied ML workflows that transform raw Internet telemetry into usable context for internal and external products.
• Collaborate with engineering, research, security, and product teams to optimize models and feedback loops.
• Develop core components including feature pipelines, training datasets, evaluation frameworks, and confidence scoring systems.

Requirements

• 5+ years of experience in data science, machine learning engineering, or software engineering with applied ML responsibilities.
• Proven experience building and deploying ML or statistical models in production environments.
• Proficiency in Go and Python, with strong software engineering practices for maintainable systems.
• Experience with large-scale data pipelines for feature generation and inference.
• Strong knowledge of supervised and unsupervised learning (classification, clustering, anomaly detection).
• Ability to evaluate models using sound statistics and manage tradeoffs between precision and recall.

Nice to have

• Experience building labeling systems for messy or partially labeled data.
• Experience with Kubernetes and cloud providers (AWS, Azure, or GCP).
• Familiarity with MLOps workflows, feature stores, and experiment tracking tools.
• Knowledge of Internet measurement or network-derived datasets.

Culture & Benefits

• Competitive benefits including equity, health, dental, and vision coverage.
• Retirement plan with company contribution and professional development stipend.
• Flexible PTO and parental leave.
• Mental health and wellness benefits.
• Inclusive environment that values diversity and global perspectives.