Job Overview
Location
Remote
Job Type
Full-time
Category
Engineering
Date Posted
May 8, 2026
Full Job Description
đź“‹ Description
- • As a Staff Machine Learning Engineer at Material Security, you will design, build, train, and deploy machine learning models to detect security-relevant threats such as phishing emails and sensitive data exposure, directly contributing to the protection of users’ privacy and inboxes from breaches and fraud.
- • Your day-to-day responsibilities include writing production-level code to convert ML models into scalable pipelines, architecting reliable and maintainable ML systems, participating in code reviews, and collaborating with cross-functional teams including product managers, designers, data scientists, and software engineers to align ML initiatives with business goals.
- • You will explore advancements in generative AI and LLMs to enhance detection capabilities, stay current with emerging algorithms and frameworks, and contribute to a strong engineering culture through mentorship and active participation in knowledge sharing.
- • Material Security is a remote-first company with an office in San Francisco, composed of world-class engineers focused on safeguarding user data and privacy through innovative security solutions. In this role, you will have the opportunity to lead end-to-end ML workflows, influence technical direction, and grow as a technical leader while working on high-impact problems in cybersecurity.
- • You will gain deep experience in applying ML to real-world security challenges, refine your expertise in LLMs and generative AI, and strengthen your ability to build and maintain production-grade ML systems at scale.
🎯 Requirements
- • B.S., M.S., or Ph.D. in Computer Science or a related technical field, or equivalent relevant work experience.
- • 8+ years of experience in machine learning, data science, or related fields (or Ph.D. with 6+ years), including at least 3 years in a senior or staff engineering role.
- • Deep understanding of supervised and unsupervised learning techniques, LLMs, and practical experience building end-to-end ML workflows from conception to deployment and maintenance.
- • Strong experience writing efficient data pipelines and production-level code using ML libraries such as scikit-learn and Pandas.
- • Experience with cloud platforms (AWS, GCP) and containerization tools (Docker, Kubernetes) is a nice-to-have.
- • Familiarity with API development (e.g., FastAPI) and text embedding modeling is a nice-to-have.
🏖️ Benefits
- • Remote-first work environment with flexibility to work from anywhere, supported by an office in San Francisco for those who prefer hybrid arrangements.
- • Competitive compensation range of $225,000–$255,000, determined by skills, experience, and qualifications.
- • Opportunity to work on cutting-edge security problems using generative AI and LLMs to protect users from phishing, fraud, and account takeover.
- • Collaborative, inclusive culture that values mentorship, knowledge sharing, and engineering excellence.
- • Equal opportunity employer committed to diversity, equity, and inclusion in all employment practices.
Skills & Technologies
About Material Security Inc.
Material Security is a cloud-native security company focused on protecting sensitive data. They offer a data security platform that provides comprehensive visibility, control, and protection for data across various cloud applications and services. Their solution aims to address the challenges of data sprawl and the increasing sophistication of data security threats. Material Security's platform enables organizations to understand where their sensitive data resides, who has access to it, and how it is being used, thereby preventing data breaches and ensuring compliance with data privacy regulations. They serve businesses looking to enhance their data security posture in the modern cloud environment.
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