Machine Learning Operations Engineer in ZeroFox

Opportunity Overview

At ZeroFox, we are passionate about bringing world-class protection to the digital-first world. Together, we have built a system capable of collecting and analyzing data from all over the internet, creating a paradigm-shifting cybersecurity product that helps secure and protect our customers and improves the global threat landscape.

We are a team of software engineers, cybersecurity experts, and data scientists who continue to develop unparalleled solutions for the cyber security industry by providing the best Digital Risk Protection SaaS in the global market. Our company, services, and user base are growing faster than ever and we’d like you to help us innovate. We believe the greatest solutions in the Digital Risk Protection space come from composing teams with varied backgrounds and experiences that can use their complementary skill sets to come up with the best market-defining solutions.

• Collaborate with industry experts across security, machine learning, digital risk protection, and cyber threat intelligence to support and optimize the machine learning solutions for the ZeroFox platform.
• Design, implement, and maintain reliable and scalable ML infrastructure that drives our AI products, enabling our Machine Learning Engineers to develop advanced machine learning models, including for NLP and computer vision applications.
• Work closely with Machine Learning Engineers to understand and enable the ML lifecycle, ensuring that they have the right tools and resources to carry out their work effectively and efficiently.
• Stay up-to-date with the latest advancements in MLOps, including data management, experiment tracking, model deployment, scaling and reliability, and monitoring practices, to integrate them into our solutions.
• Collaborate with product managers, data analysts, and software engineers to seamlessly integrate ML models into the ZeroFox platform and ensure their smooth operation.
• Maintain clear and well-documented code to ensure long-term sustainability and facilitate smooth collaboration with other team members.

• Motivated, communicative, teamwork-oriented professionals who are comfortable working in agile environments and are able to learn and adapt quickly
• Bachelor’s degree in computer science, data science, software engineering, or a related field, OR equivalent education or experience
• Experience in MLOps, DevOps, DataOps, or similar roles, typically a minimum of 3 years
• Advanced scripting experience, typically a minimum of 2 years
• Experience in Python or Go
• Experience supporting the machine learning lifecycle, including versioning, monitoring, and deployment
• Strong understanding of data structures and algorithms
• Solid software engineering design and implementation skills at the level of an individual component (e.g. consisting of many classes and functions)
• Experience building and scaling systems with cloud platforms such as AWS, Google Cloud, or Azure
• Experience with containerization technologies such as Docker, Nomad and Kubernetes
• Strong knowledge of infrastructure as code tools, such as Terraform (preferred) or AWS CloudFormation
• Ability to troubleshoot complex networking issues in a cloud environment
• Good communication, collaboration, and presentation skills in English
• Ability to work effectively in a fast-paced, agile environment.

• Experience with ML workflow tools, like MLflow and SageMaker
• Familiarity with machine learning frameworks like PyTorch, TensorFlow, or similar
• Applied knowledge of distributed computing and big data architectures
• Deep knowledge of good software engineering practices
• Knowledge of CI/CD pipelines and version control systems like Git
• We also value equivalent experience to these languages, frameworks, and tools. If you think you might be a fit, apply!

• Opportunities to learn and contribute your knowledge to our Digital Risk Protection platform
• Competitive compensation
• Competitive PTO
• Complementary health insurance
• Daily catered lunches for in-office work
• Respectful and nourishing work environment, where every opinion is heard and everyone is encouraged to be an active part of the organizational culture.
• Regular team bonding activities like cooking and cocktails classes, bingos, stand up comedy, magic shows, virtual happy hour, lunch and learns, etc.
• Additional Parental Leave
• Excellent communication: between teams, people, organizations and leaders