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Senior Machine Learning Engineer

3 weeks, 5 days ago
United States, Canada
Full-time
Senior
Machine Learning Engineer
Software Development
AWS Azure Feature Engineering GCP Go Kubernetes Machine Learning MLOps Python
Apply Now
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
View All Jobs 13

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 turn raw Internet telemetry into usable context.
  • Partner with engineering, research, security, and product teams to define the right models, datasets, and feedback loops.
  • Develop 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 relationships to 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 and/or Python, with 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 such as classification, clustering, similarity scoring, or anomaly detection.
  • Ability to evaluate models using sound statistics and understand tradeoffs among precision, recall, accuracy, and confidence.
  • Ability to write understandable, testable code with an eye toward maintainability.
  • Strong communication skills and the ability to explain technical concepts, model behavior, and tradeoffs to engineers, researchers, and product managers.
  • Experience building classification, enrichment, or labeling systems for messy or partially labeled data is preferred.
  • Experience deploying models in containerized environments such as Kubernetes is preferred.
  • Experience with a cloud provider such as AWS, Azure, or GCP is preferred.
  • Familiarity with feature stores, model serving, MLOps workflows, or experiment tracking tools is preferred.
  • Familiarity with security, Internet measurement, or network-derived datasets is preferred.

Benefits

  • Remote work within the United States, with remote employees also open across the continental US or Canada.
  • Salary range of $171,000-$203,000 for high cost of living areas, plus bonus eligibility and equity.
  • Salary range of $150,000-$188,000 for all other locations, plus bonus eligibility and equity.
  • Benefits effective on day one.
  • 401(k) match.
  • Health, vision, and dental coverage.

Interested in this position?

Apply directly on the company website

Apply Now

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