Job description

WHAT IS 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. We help companies thrive in the new AI-first era of business. 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. By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift. WHY BOX NEEDS YOU Box Shield is an add-on security layer that protects the flow of information and reduces content-centric risk without adding friction. It uses classification-based controls to prevent data loss and AI-powered, context-aware alerts to detect malware, compromised accounts, and malicious behavior at scale. Shield’s mission is to secure enterprise content while delivering a seamless user experience, ensuring Box remains the platform of choice for secure Intelligent Content Management. Shield keeps customer content safe by surfacing malware, compromised accounts, and anomalous behavior early, giving administrators the context they need to take proactive action before incidents escalate. The Shield team is hiring Machine Learning engineers to build and scale ML systems that safeguard millions of users and billions of files from ransomware, data exfiltration, insider threats, and emerging AI-based attacks. As part of a fast-paced backend/core team, you’ll collaborate across Box to ship future-proof security capabilities for high-demand use cases. WHAT YOU'LL DO Build Threat Detection Models: Design, train, and deploy ML models for ransomware detection, suspicious session identification, and user behavior analytics Scale Data Pipelines: Own end-to-end ML pipelines that process high-volume security event streams using Apache Spark, GCP Dataflow, and Vertex AI Feature Engineering: Create and maintain feature stores that power real-time and batch anomaly detection systems Production ML Systems: Deploy, monitor, and iterate on ML models in production, serving enterprise customers at scale Cross-functional Collaboration: Partner with Platform, Application Engineering, and Product teams to translate security requirements into ML solutions Participate in our on-call rotation, available at all times while on-call to help respond to and triage any issues that arise. WHO YOU ARE We are an AI-first company. This means you approach your work with a growth mindset and find ways to leverage AI to help make faster, smarter decisions that will 10X your impact at Box. Must Have Experience 3+ years of experience in applied machine learning Strong programming skills in Python Deployed and maintained ML models serving real traffic Experience with GCP (Vertex AI, BigQuery, Dataflow) or equivalent (AWS SageMaker, Azure ML) Deep understanding of feature engineering, model evaluation, and MLOps Strong communication skills with ability to explain complex ML concepts to non-technical stakeholders Nice To Have Experience Experience in security/threat detection, anomaly detection, or fraud detection Experience with sequential data, anomaly detection, or behavioral modeling (time-series forecasting, LSTM, Transformers, or similar) Knowledge of LLMs and AI safety (prompt injection, guardrails, red-teaming) Experience with streaming/real-time ML systems Familiarity with Java for service integrations Publications or contributions in ML security Tech Stack You’ll Work With Languages: Python, Scala, 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 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.Your Recruiter will share more about how we work and company culture during the hiring process. At Box, we believe unique and diverse experiences benefit our culture, our products, our customers, our company, and our world. We aim to recruit a passionate, high-performing workforce that reflects the world we live in. If you are head-over-heels about this role but unsure if you meet all the requirements, we encourage you to apply! EQUAL OPPORTUNITY We are an equal opportunity employer and value 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 Chair 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 Chair Ordinance. The Fair Chance Ordinance is provided here . For details on how we protect your information when you apply, please see our Personnel Privacy Notice. If you are a California-resident, please read our California Applicant & Candidate Privacy Notice here . NOTICE OF USE OF AI At Box, we believe in the power of AI to improve the recruiting process while keeping people at the heart of every decision. For more information on the use of AI in our hiring process, please visit our webpage here . 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. This role is also eligible for equity and benefits. For more information , check out our benefits and perks . In accordance with OFCCP compliance, here is the Pay Transparency Provision . Redwood City Pay Range $175,500 — $219,500 USD

Requirements

Must-haves

WHAT IS BOX?
Build Threat Detection Models: Design, train, and deploy ML models for ransomware detection, suspicious session identification, and user behavior analytics
Scale Data Pipelines: Own end-to-end ML pipelines that process high-volume security event streams using Apache Spark, GCP Dataflow, and Vertex AI
Feature Engineering: Create and maintain feature stores that power real-time and batch anomaly detection systems
Production ML Systems: Deploy, monitor, and iterate on ML models in production, serving enterprise customers at scale
Cross-functional Collaboration: Partner with Platform, Application Engineering, and Product teams to translate security requirements into ML solutions
Participate in our on-call rotation, available at all times while on-call to help respond to and triage any issues that arise.
We are an AI-first company. This means you approach your work with a growth mindset and find ways to leverage AI to help make faster, smarter decisions that will 10X your impact at Box.
Must Have Experience
3+ years of experience in applied machine learning
Strong programming skills in Python
Deployed and maintained ML models serving real traffic
Experience with GCP (Vertex AI, BigQuery, Dataflow) or equivalent (AWS SageMaker, Azure ML)
Deep understanding of feature engineering, model evaluation, and MLOps
Strong communication skills with ability to explain complex ML concepts to non-technical stakeholders
Experience in security/threat detection, anomaly detection, or fraud detection
Experience with sequential data, anomaly detection, or behavioral modeling (time-series forecasting, LSTM, Transformers, or similar)
Knowledge of LLMs and AI safety (prompt injection, guardrails, red-teaming)
Experience with streaming/real-time ML systems
Familiarity with Java for service integrations
Publications or contributions in ML security
Tech Stack You’ll Work With
Languages: Python, Scala, Java

Nice-to-haves

Nice To Have Experience

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Keywords to mirror

aimachine learningmlgcppythonawsazurejavakubernetes

Platform: greenhouse
Effort: quick

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