Senior Machine Learning Engineer

18 hours, 5 minutes ago
Full-time
Senior
Software Development
Censys

Censys

Censys provides security teams with a comprehensive and accurate mapping of the internet, enabling them to effectively defend against attack surfaces and proactively hunt for threats.

IT Services
51-250
Founded 2017
$53M raised

Description

  • Build and improve machine learning models and data-driven systems that classify, cluster, label, and enrich Internet-observed assets and services.
  • Own the design and development of applied ML workflows that transform raw Internet telemetry into usable context.
  • Partner with engineering, research, security, and product teams to define models, datasets, and feedback loops that improve coverage and quality.
  • Develop components such as feature pipelines, training datasets, model evaluation frameworks, confidence scoring systems, and cloud or on-prem services.
  • Help expand the data platform to support future products and features that add richer context and reveal complex relationships in Internet data.

Requirements

  • 5+ years of experience in data science, machine learning engineering, or software engineering with applied ML responsibilities.
  • Experience building and deploying machine learning or statistical models in production environments.
  • Experience programming in Go or Python and familiarity with software engineering practices for maintainable systems.
  • Experience working with large datasets and building data pipelines for feature generation, training, or inference.
  • Proficiency with supervised and unsupervised learning techniques, including classification, clustering, similarity scoring, or anomaly detection.
  • Ability to evaluate models using statistics and understand tradeoffs among precision, recall, accuracy, and confidence.
  • Ability to write understandable, testable code with an emphasis on maintainability.
  • Strong communication skills and ability to explain technical concepts, model behavior, and tradeoffs to engineers, researchers, and product managers.
  • Open to using AI responsibly to improve efficiency and impact.
  • Experience building classification, enrichment, or labeling systems for messy or partially labeled data (preferred).
  • Experience deploying models in containerized environments such as Kubernetes (preferred).
  • Experience with a cloud provider such as AWS, Azure, or GCP (preferred).
  • Familiarity with feature stores, model serving, MLOps workflows, or experiment-tracking tools (preferred).
  • Familiarity with security, Internet measurement, or network-derived datasets (preferred).

Benefits

  • Remote work within the United States.
  • Competitive salary range of $171,000-$203,000 in high-cost locations or $150,000-$188,000 elsewhere, plus bonus eligibility and equity.
  • Equity compensation.
  • Health, dental, and vision coverage.
  • Retirement plan with company contribution.
  • Parental leave.
  • Mental health and wellness benefits.
  • Flexible PTO.
  • Professional development stipend.
  • Annual bonus plan for eligible non-sales roles.

Interested in this position?

Apply directly on the company website

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