Senior Machine Learning Engineer, Censys

• 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

Desirable

• We’re looking to hire a Senior Machine Learning Engineer to build models and data-driven systems that help classify, label, and enrich vast amounts of Internet data, providing direct value to customers and other parts of our organization
• Censys operates distributed infrastructure for Internet-wide scanning and you will help us continue our mission to transform raw Internet telemetry into high-quality datasets, classifications, and insights about the Internet at large
• At Censys, we believe in working iteratively, while keeping the big picture in mind
• We’re expanding our data platform to enable future products and features that make the Internet more explainable by adding richer context and showing complex relationships
• We’re looking for someone who is curious, collaborative, and excited to grow while contributing to our mission
• 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