Senior ML Engineer - Remote, Internet Data & Security

JoinStartup; United States; Remote; USD 151,000 - 191,000; Full time

Benefits offered by this job

Equity

Health, dental & vision

Retirement plan with company match

Parental leave

Mental health benefits

Flexible PTO

Professional development stipend

Job summary

Censys is seeking a Senior Machine Learning Engineer to build models and data-driven systems that classify, label, and enrich Internet-observed assets. You will work on distributed infrastructure for Internet-wide scanning and contribute to datasets, classifications, and insights for internal and customer-facing products.

The role emphasizes collaboration with engineering, security, and product teams, with a focus on scalable ML workflows, feature pipelines, and model evaluation in cloud or

Qualifications

• 5+ years in data science or ML engineering with applied ML
• Experience deploying ML models in production
• Proficiency in Go/Python and scalable software engineering
• Experience with large datasets and data pipelines
• Strong statistical evaluation and understanding of precision/recall tradeoffs
• Ability to write clean, testable code
• Excellent communication of technical concepts to engineers/researchers/product managers

Responsibilities

• Build and improve machine learning models and data-driven systems
• Own the design and development of applied ML workflows
• Partner with engineering, research, security, and product teams to ensure quality
• Contribute across feature pipelines, training datasets, model evaluation, and deployment services

Skills

Data science

ML engineering

Python

Go

Data pipelines

Model evaluation

Statistics

Communication

Tools

Kubernetes

AWS

Azure

GCP

MLOps tools

Model serving

Job description

Censys is seeking a Senior Machine Learning Engineer to build models and data-driven systems that classify, label, and enrich Internet-observed assets. You will work on distributed infrastructure for Internet-wide scanning and contribute to datasets, classifications, and insights for internal and customer-facing products.

The role emphasizes collaboration with engineering, security, and product teams, with a focus on scalable ML workflows, feature pipelines, and model evaluation in cloud or