Staff Machine Learning Engineer, Shield

Sorry, this job was removed at 08:49 p.m. (CST) on Tuesday, Jun 18, 2024
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Redwood City, CA
Hybrid
245K-307K Annually
5-7 Years Experience
Cloud • Information Technology • Software
The Role

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, and workflow. We have an amazing opportunity to further establish ourselves as leaders in the space, and 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 and 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 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

  • Develop and enhance anomaly detection algorithms by applying advanced machine learning techniques and statistical modeling
  • Implement and optimize algorithms and models to improve accuracy, speed, and scalability
  • Analyze large-scale data sets to gain insights and identify opportunities for improvement in threat detection
  • Conduct experiments, A/B testing, and evaluations to measure the performance and effectiveness of different algorithms and models
  • Keep up-to-date with the latest research and advancements in the field of security and machine learning, and apply relevant techniques to solve real-world problems
  • Help drive architectural, product and technological decisions for security-focused products
  • Influence our team's processes and execution methods, leading by example with high-quality code and 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 and inclusiveness, we aim to execute quickly, and 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 and 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 and strive to do work you're proud of, both technically and in your team interactions
  • You are able to inspire other people to work with you, and you enjoy mentoring and coaching, as well as learning from other engineers
  • You've built, deployed, and supported machine learning systems at scale
  • You have strong analytical and problem-solving skills, with the ability to work with large and complex datasets
  • You are passionate about digging into the “why” of customer problems, to develop an elegant and scalable solution
  • You understand data and metrics are the foundation of ML and work with others to ensure the right information is available

REQUIRED EXPERIENCE

  • Proficiency in Python and 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) and libraries (e.g., scikit-learn, NumPy, pandas)
  • Strong understanding of statistical modeling, data structures, and 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, and semi-supervised learning
  • Familiarity with deep learning techniques and frameworks
  • Publications or contributions to the machine learning community

You are in an office based role with the expectation of working from the Redwood City, CA office a minimum of 2x/week.

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 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 on benefits, check out our healthcare benefits and additional Box Benefits + Perks.

 

In accordance with OFCCP compliance, here is the Pay Transparency Provision. 

United States Pay Range

$245,000$306,500 USD

The Company
HQ: Redwood City, CA
2,500 Employees
Hybrid Workplace
Year Founded: 2005

What We Do

Box (NYSE:BOX) is the leading Content Cloud, a single platform that empowers organizations to manage the entire content lifecycle, work securely from anywhere, and integrate across best of breed apps. Founded in 2005, Box simplifies work for leading global organizations, including AstraZeneca, JLL, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia. Visit box.com to learn more. And visit box.org to learn more about how Box empowers nonprofits to fulfill their missions.

Why Work With Us

We have an inclusive culture that is based on development and growth. We value our people as individuals and know that they can make an impact when properly empowered. We fill 30% of all of our open positions with internal people. Everyone is an owner and we are candid with each other in order to learn.

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