Materialsecurity is hiring a Staff Machine Learning Engineer to join their AI / Machine Learning team. 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). Key skills: AWS, GCP, Docker, Kubernetes, Machine Learning.
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).
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.
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.
Deep understanding of supervised/unsupervised learning techniques and LLMs
Strong experience writing efficient and effective data pipelines.
Practical knowledge of how to build efficient end-to-end ML workflows and a strong drive to won the entire process of model development from conception through deployment, to maintenance..
Experience with machine learning libraries (e.g., scikit, Pandas)
Nice to have
Experience in API development on top of a fast API
Experience tracking text embedding modeling
Strong knowledge of cloud platforms (e.g., AWS, GCP) and containerization tools (e.g., Docker, Kubernetes).
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Material Security is a remote-first workplace with an office in San Francisco, California.
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Compensation at Material Security is determined by a range of factors, including but not limited to the individual’s particular combination of knowledge, skills, competencies, and experience. The projected compensation range for this position is $225,000-255,000.
Equal Opportunity Employer Statement
Material Security is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, disability, genetic information, or any other legally protected status. All employment decisions are based on qualifications, merit, and business needs.
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