WHAT IS BOX

Box is the market leader for Cloud Content Management. Our mission is to power how the world works together. Box is partnering with enterprise organizations to accelerate their digital transformation by creating a single platform for secure content management, collaboration, & workflow. We have an amazing opportunity to further establish ourselves as leaders in the space, & we need strong advocates to help us achieve that goal.

By joining Box, you will have the unique opportunity to help capture a majority of this developing market & define what content management looks like for the digital enterprise. Today, Box powers 100,000+ businesses, including many top Fortune 500 companies who trust our secure collaboration platform to manage the entire content lifecycle.

WHY BOX NEEDS YOU

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 & easy-to-use way. Shields mission is to protect the flow of an enterprises 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, & 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 Boxs customers protect their Box content. Security being a horizontal product, you will work across teams to design & implement capabilities that power high-demand use-cases in a future-proof way.

WHAT YOU'LL DO

• Develop & enhance anomaly detection algorithms by applying advanced machine learning techniques & statistical modeling
• Implement & optimize algorithms & models to improve accuracy, speed, & scalability
• Analyze large-scale data sets to gain insights & identify opportunities for improvement in threat detection
• Conduct experiments, A/B testing, & evaluations to measure the performance & effectiveness of different algorithms & models
• Keep up-to-date with the latest research & advancements in the field of security & machine learning, & apply relevant techniques to solve real-world problems
• Help drive architectural, product & technological decisions for security-focused products
• Influence our team's processes & execution methods, leading by example with high-quality code & coaching junior team members

WHO YOU ARE

You believe Security is core to enterprise products. In addition to influencing the technical vision for the team, you also want to have a voice in the product vision. You are interested in building new capabilities into our Box offering. At Box, we strive to foster a culture of transparency & inclusiveness, we aim to execute quickly, & we are committed to doing the right thing for our end users. We value team members who are lifelong learners, passionate about continuous improvement for themselves & for the team around them. You'll join a highly collaborative scrum team that is very passionate about the security mission. You'll have an opportunity to drive impactful feature development from the beginning to the end. And the work you'll do will directly impact the experience of our 40 million+ users.

• You are passionate about solving hard machine learning problems using data-driven solutions
• You like to be an owner & strive to do work you're proud of, both technically & in your team interactions
• You are able to inspire other people to work with you, & you enjoy mentoring & coaching, as well as learning from other engineers
• You've built, deployed, & supported machine learning systems at scale
• You have strong analytical & problem-solving skills, with the ability to work with large & complex datasets
• You are passionate about digging into the why of customer problems, to develop an elegant & scalable solution
• You understand data & metrics are the foundation of ML & work with others to ensure the right information is available

REQUIRED EXPERIENCE

• Proficiency in Python & Jupyter Notebooks
• Familiarity with at least one object oriented language like C, C++, Java, Scala
• Master's degree in Computer Science, Mathematics, Statistics, or a related
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) & libraries (e.g., scikit-learn, NumPy, pandas)
• Strong understanding of statistical modeling, data structures, & algorithms
• 5+ years of industry experience in machine learning or related field, or 3+ with advanced degree

NICE TO HAVE EXPERIENCE 

• Ph.D. in Computer Science, Mathematics, Statistics, or a related field, with a focus on machine learning
• Familiarity with anomaly detection, time-series analysis, graph-based machine learning, & semi-supervised learning
• Familiarity with deep learning techniques & frameworks
• Publications or contributions to the machine learning community

EQUAL OPPORTUNITY

We are an equal opportunity employer & 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, & any other protected ground of discrimination under applicable human rights legislation. Box strives to respect the dignity & independence of people with disabilities & is committed to giving them the same opportunity to succeed as all other employees. Inclusiveness is core to our culture at Box, & 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 & beyond.

Notice to applicants in San Francisco:  Box, Inc & 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.