Senior Machine Learning Engineer
Censys is seeking a Senior Machine Learning Engineer to join our team and contribute to transforming raw Internet telemetry into high-quality datasets and insights. This role involves building and enhancing machine learning models and data-driven systems that classify, label, and enrich vast amounts of Internet data, providing direct value to our customers and organization. As part of a collaborative and creative team, you will work closely with data scientists, engineers, and product teams to develop scalable systems that enhance how customers interact with and understand our data.
In this position, you will be responsible for building and improving machine learning models and data-driven systems that classify, cluster, label, and enrich Internet-observed assets and services. You will own the design and development of applied ML workflows that turn raw Internet telemetry into usable context for internal systems and customer-facing products. Collaboration with engineering, research, security, and product teams is essential to ensure the development of the right models, datasets, and feedback loops to improve coverage and quality. Your expertise in machine learning, data science, and software engineering will be leveraged to build various system components, including feature pipelines, training datasets, model evaluation frameworks, confidence scoring systems, and services that run in the cloud or on-premises.
The ideal candidate will have over 5 years of experience in data science, machine learning engineering, or software engineering with applied ML responsibilities. Proficiency in building and deploying machine learning or statistical models in production environments is required. Strong programming skills in Go and Python, along with familiarity with software engineering practices for building maintainable systems, are essential. Experience working with large datasets and building data pipelines for feature generation, training, or inference is necessary. A solid understanding of supervised and unsupervised learning techniques, such as classification, clustering, similarity scoring, or anomaly detection, is expected. The ability to evaluate models using sound statistics and understand trade-offs related to precision, recall, accuracy, and confidence is crucial. Strong communication skills are also important, as you will need to explain technical concepts, model behavior, and trade-offs to engineers, researchers, and product managers.
For high cost of living areas (San Francisco Bay Area, Seattle, and the New York City metro), the expected salary range for this position is $171,000 - $203,000, plus bonus eligibility and equity. For all other locations, the expected salary range is $150,000 - $188,000, plus bonus eligibility and equity. In addition to a competitive compensation package, our benefits are effective on day one and include, but are not limited to, a 401k match, health, vision, dental, and more.
Censys is a rapidly growing cybersecurity startup based in Ann Arbor, Michigan, with a mission to provide real-time Internet intelligence and actionable threat insights to global governments, over 50% of the Fortune 500, and leading threat intelligence providers worldwide. Our innovation is fueled by the team’s global perspectives and diverse backgrounds. We welcome healthy debate, constructive conversations, and outside-the-box thinking to ensure we are moving fast, learning, and iterating quickly. Joining Censys offers the opportunity to work in a dynamic environment where your contributions directly impact the security posture of organizations worldwide.