Senior Machine Learning Engineer, Shield

About Box

Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia.

About Box Shield

Box Shield is an add-on security control that helps protect the flow of information and reduce content-centric risks with precision — without slowing down work. It allows classification-based security controls to automatically prevent data loss, and AI-powered, context-aware alerts to detect potential data theft and malicious content. Box Shield enables secure hybrid work from anywhere, anytime, and any device with native tools that help secure content at scale.

The Shield team is looking for ML engineers with a passion for building out enterprise security features that are able to handle complex use-cases in a robust and easy-to-use way. Shield's mission is to protect the flow of an enterprise's information while delivering frictionless user experience so that Box is the tool of choice for secure Cloud Content Management. Shield helps customers keep their content secure by detecting malicious software in their content, potentially compromised accounts, and anomalous behavior so that Administrators have the right information to act before a problem occurs.

Responsibilities

• Build threat detection models: design, train, and deploy ML models for ransomware detection, suspicious session identification, and user behavior analytics, anomaly detection
• Scale data pipelines: own end-to-end ML pipelines that process high-volume security event streams using Apache Spark, GCP Dataflow, GCP Dataproc, BigQuery and Vertex AI
• Create and maintain feature stores that power real-time and batch anomaly detection systems
• Deploy, monitor, and iterate on ML models in production, serving enterprise customers at scale
• Partner with Platform, Application Engineering, and Product teams to translate security requirements into ML solutions
• Participate in on-call rotation, available at all times while on-call to help respond to and triage any issues that arise

Required Experience

• 5+ years of experience in applied machine learning
• Lead design and implementation efforts in building, deploying and supporting scalable ML systems
• Experience with GCP (Vertex AI, BigQuery, Dataflow) or equivalent (AWS SageMaker, Azure ML)
• Strong communication skills with ability to explain complex ML concepts to non-technical stakeholders
• Ownership mindset with focus on delivering high-quality work both technically & collaboratively
• Bachelor's degree or above in Computer Science or equivalent practical experience
• Strong programming skills in Python
• Deployed and maintained ML models serving real traffic
• Deep understanding of feature engineering, model evaluation, and MLOps
• Clear, inclusive communicator who values collaboration, mentorship, and continuous improvement

Nice to Have Experience

• Experience in security/threat or fraud detection and with sequential data and behavioral modeling (e.g., anomaly detection, time-series forecasting, LSTM, Transformers, or similar)
• Experience with streaming/real-time ML systems
• Experience with FedRAMP/compliance-constrained environments
• Familiarity with Java stack for service integrations
• Publications or contributions in ML security

Tech Stack

• Languages: Python, Go, Java
• ML/Data: Apache Spark, Vertex AI, BigQuery, TensorFlow/PyTorch
• Infrastructure: GCP, Kubernetes
• Domains: User Behavior Analytics, Time-Series Anomaly Detection, AI Security, Content classification, Ransomware Detection

Work Environment

Box lives its values, with community and in-person collaboration being a core part of our culture. Boxers are expected to work from their assigned office a minimum of 3 days per week.

Compensation & Benefits

• United States Pay Range: $211,000–$263,500 USD
• This role is also eligible for equity and benefits

Equal Opportunity

Box is an equal opportunity employer and values diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability, and any other protected ground of discrimination under applicable human rights legislation. Box strives to respect the dignity and independence of people with disabilities and is committed to giving them the same opportunity to succeed as all other employees. Inclusiveness is core to our culture at Box, and we strive to ensure you get the most from your interview experience.

Box makes reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please complete this form. Reasonable accommodations may include scheduling adjustments, document dictation and beyond.

Notice to applicants in Los Angeles: Box, Inc and its related branches will consider for employment, qualified applicants with criminal histories in a manner consistent with the Los Angeles Fair Chance Ordinance. The Fair Chance Ordinance is provided here.

Notice to applicants in San Francisco: Box, Inc and its related branches will consider for employment, qualified applicants with criminal histories in a manner consistent with the San Francisco Fair Chance Ordinance. The Fair Chance Ordinance is provided here.

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Box is committed to fair and equitable compensation practices. Actual base salary (or OTE if commissionable role) is dependent upon factors such as: knowledge, skill level, experience, and work location.