Senior Machine Learning Engineer, Shield

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 control that helps you 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. As an engineer on our team, you will join a diverse, fast-paced, mainly backend/core team that works together to build new capabilities that help Box’s customers protect their Box content. Security being a horizontal product, you will work across teams to design and implement capabilities that power high-demand use-cases in a future-proof way.

WHAT YOU'LL DO

• 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


• 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.

• 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

MUST-HAVE EXPERIENCE

• Bachelors or above degree 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 You’ll Work With

• 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

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 .

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 . 

United States Pay Range

$211,000 - $263,500 USD