Senior Machine Learning Engineer

Job not on LinkedIn

🕒 May 15

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Censys

51 - 200 employees

Founded 2017

🔒 Cybersecurity

🏢 Enterprise

Cybersecurity • Enterprise • Data

Censys is a leading Internet Intelligence Platform that specializes in Threat Hunting and Attack Surface Management. It provides security teams with a comprehensive, accurate, and up-to-date map of the internet to defend against attacks and hunt for threats. Censys offers solutions for Cloud Asset Discovery, Exposure and Risk Management, and External Attack Surface Management. Its proprietary Internet Map delivers detailed insights and extensive internet scanning capabilities, allowing organizations to continuously monitor internal and external attack surfaces. Founded by the creators of ZMap at the University of Michigan, Censys is deeply rooted in the security open source community and boasts a large internet intelligence community. Censys empowers organizations, including those in financial services, government, and healthcare, to act swiftly against evolving threats and protect their internet-facing assets effectively.

📋 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 for internal systems and customer-facing products. • Partner with engineering, research, security, and product teams to ensure we’re building the right models, datasets, and feedback loops to improve coverage and quality. • Leverage your experience in machine learning, data science, and software engineering to build various parts of the system, including components like: feature pipelines, training datasets, model evaluation frameworks, confidence scoring systems, and services that run in the cloud or on-prem.

🎯 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/Python, and familiarity with software engineering practices for building 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 related to precision, recall, accuracy, and confidence. • Ability to write understandable, testable code with an eye towards maintainability. • Possess strong communication skills and can explain technical concepts, model behavior, and tradeoffs to engineers, researchers, and product managers. • Open to using AI to amplify their skills and strengthen their work - demonstrating curiosity, a willingness to learn, and sound judgment in applying AI responsibly to improve efficiency and impact.

🏖️ Benefits

• Equity • Health, dental & vision coverage • Retirement with company contribution • Parental leave • Mental health & wellness benefits • Flexible PTO • Professional development stipend • Sales incentive pay for most sales roles • Annual bonus plan for eligible non-sales roles

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