It's fun to work in a company where people truly BELIEVE in what they're doing!

We're committed to bringing passion and customer focus to the business.

This is a remote, full-time position. 

About the Organization

ML Labs is an internal machine learning group that consults across Proofpoint's entire product portfolio. Over the past several years, our teams have developed data-driven product features, leveraging a range of model architectures from tree-based models to state-of-the-art Transformers. Each new project surfaces novel puzzles to be solved, while production deployments to our cloud ML Platform expose new MLOps challenges. Recently, our organization began spearheading company-wide initiatives around large language models and their applications to the business by creating resources, putting together project teams, and organizing hackdays.

About the Team

The Protection team has produced features enabled by machine learning since early 2022 for three different Proofpoint products: Digital Risk (3 models in production), Cloud Protection (1 model in production), and Enterprise DLP (2 models slated for production). We are a small but growing team with ample opportunities for ownership and impact, guided by our four values:

• Human Beings, Not Human Doings: We bring our whole self into every part of our work. We possess worth and value beyond our code.

• Humble But Confident: We are confident in our current abilities while celebrating the strengths of our team and our own areas for growth.

• Openly Collaborative: We strive for pristine documentation, transparent chat rooms, and realistic management of tech debt and tribal knowledge.

• Impactful Innovators:We seek and scope meaningful work that we approach creatively but efficiently.

We currently have three technical members and are looking to add a Senior or Staff data scientist as described below.

What You'll Do:

• Mentor junior data scientists across ML Labs through individual project meeting and technical deep dives

• Support junior technical members on the Protection Team in modeling decisions within the Digital Risk and Cloud Protection spaces

• Build out more ML-enabled features within the Enterprise DLP and Cloud Protection spaces

• Participate in shaping and executing the Large Language Model strategy for our organization and for Proofpoint

• Coach summer and academic year interns through their project selection and technical decisions

What You’ll Need:

• A proven track record for mentoring technical members in a professional setting

• A deep understanding of recent computer vision and natural language processing algorithms and architectures

• Fluency in the Python machine learning life cycle: designing, developing, deploying and maintaining models in production

• Proficiency in Linux commands, version control, unit testing, and containerization

• A strong grasp of traditional machine learning algorithms, both unsupervised and supervised

• Concrete rhythms for staying current with the rapidly evolving field of machine learning

• The ability to communicate concisely with a non-technical audience

• The ability to collaborate frictionlessly with a wide range of technical collaborators, both inside and outside the team

• The ability to manage several projects simultaneously, including scoping technical tasks and effectively communicating progress toward milestones

• A minimum of 5 years of industry experience (graduate work will be excluded)

What Will Help:

• Previous professional experience at a SaaS company

• Knowledge of infrastructure-as-code tools such as CloudFormation or Terraform and public cloud services such as AWS or Azure

• A graduate degree in Statistics, Machine Learning, Computer Science, or technical field

• Interest in computer, network, or email security

#LI-PH

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

Consistent with Proofpoint values and applicable law, we provide the following information to promote pay transparency and equity. Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets as set out below. Pay within these ranges varies and depends on job-related knowledge, skills, and experience. The actual offer will be based on the individual candidate. The range provided may represent a candidate range and may not reflect the full range for an individual tenured employee. This role may be eligible for variable pay and/or equity. We offer a competitive benefits package that includes flexible time off, a robust well-being program that provides for 4 global wellbeing days per year, and a 3-week work from anywhere option.

Base Pay Ranges:

SF Bay Area, New York City Metro Area:

California (excludes SF Bay Area), Colorado, Connecticut, Illinois, Washington DC Metro, Maryland, Massachusetts, New Jersey, Texas, Washington, Virginia, and Alaska:

All other cities and states excluding those listed above: