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Staff Machine Learning Engineer

Material Security - Remote, San Francisco, CA, USA

Posted May 13, 2026

Benefits

Parental leave
Not verified
Non-birth-parent leave
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Family-building benefits
  • Fertility benefits: Not verified
  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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Verification
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Salary
$225K-$255K From the posting source checked Jun 20, 2026
401(k) match
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Market context

U.S. role benchmark (BLS OEWS)
$116,543 U.S. median for this role
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

106% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Engineering From the posting source checked Jun 20, 2026
Seniority
Staff Plus From the posting source checked Jun 20, 2026
Work mode
Remote From the posting source checked Jun 20, 2026
In-office days
0 days From the posting source checked Jun 20, 2026

Schedule

Shift type
Not verified
Weekend work
Not verified

Company

Company stage
Early From the posting source checked Jun 20, 2026

Application

Cover letter
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Assessment
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Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Staff Machine Learning Engineer Remote, San Francisco, CA, USA As a Machine Learning Engineer at Material Security, you'll be part of a team of experienced, world-class engineers, working to protect our users and their privacy (e.g., inboxes from breaches, targeted phishing, fraud, and lateral account takeover). Your mission is to build, deploy, and maintain high quality models that detect security relevant data and behavior (phishing emails, sensitive data in email and drives). Responsibilities - Design, build, train, and deploy machine learning models to detect sensitive data and malicious threats (phishing emails). - Write production-level code to convert your ML models into working pipelines and participate in code reviews to ensure code quality and distribute knowledge. - Architect scalable, reliable, and maintainable machine learning pipelines, integrating seamlessly with existing backend systems. - Explore recent advancements in generative AI and LLMs as potential additions to our detection capabilities. - Work closely with machine learning engineers, product managers, designers, data scientists, and software engineers to align machine learning initiatives with business goals. - Stay ahead of the curve by exploring new algorithms, technologies, and frameworks to enhance our detection models. - Contribute to great engineering culture through active participation and mentorship. What We're Looking For Must Haves - B.S., M.S. or Ph.D. in Computer Science or related technical field or relevant work experience. - 8+ years (or Ph.D. with 6+ years) of experience in machine learning, data science, or related fields, with at least 3 years in a senior or staff engineering role.

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