Senior Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and enhance machine learning models and data-driven systems that classify, cluster, label, and enrich assets and services observed on the Internet.

• Take ownership of the design and implementation of applied ML workflows that convert raw Internet telemetry into actionable context for internal systems and customer-facing products.

• Collaborate with engineering, research, security, and product teams to create suitable models, datasets, and feedback mechanisms that enhance coverage and quality.

• Construct feature pipelines, training datasets, model evaluation frameworks, confidence scoring systems, and services that operate in the cloud or on-premises.

⛳️ Requirements

• A minimum of 5 years of experience in data science, machine learning engineering, or software engineering with applied ML responsibilities.

• Proven experience in building and deploying machine learning or statistical models in production settings.

• Proficiency in programming languages such as Go and Python.

• Understanding of software engineering practices for developing maintainable systems.

• Experience working with large datasets and creating data pipelines for feature generation, training, or inference.

• Expertise in supervised and unsupervised learning techniques, including classification, clustering, similarity scoring, or anomaly detection.

• Ability to assess models using sound statistical methods and comprehend precision, recall, accuracy, and confidence trade-offs.

• Capability to produce clear, testable, and maintainable code.

• Excellent communication skills with the ability to articulate technical concepts, model behaviors, and trade-offs to engineers, researchers, and product managers.

• Experience in developing classification, enrichment, or labeling systems for complex or partially labeled data.

• Familiarity with deploying models in containerized environments like Kubernetes.

• Experience with at least one cloud provider, such as AWS, Azure, or GCP.

• Knowledge of feature stores, model serving, MLOps workflows, or experiment-tracking tools.

• Familiarity with security, Internet measurement, or datasets derived from network activities.

🏝️ Benefits

• Bonus eligibility for non-sales roles that meet the criteria.

• Equity opportunities.

• Comprehensive health, dental, and vision coverage.

• Retirement plan with company contributions.

• Parental leave benefits.

• Mental health and wellness programs.

• Flexible paid time off (PTO).

• Professional development stipend available.

• Reasonable accommodations for individuals with disabilities.

• In-person onboarding at Censys headquarters located in Ann Arbor.