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.

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.

Senior Machine Learning Engineer

Key skills