Security Engineer II (Machine Learning)

SiloSmashers; Arlington (VA); Remote; USD 80,000 - 100,000; Full time

Job summary

An innovative firm is seeking a Security Engineer to lead machine learning security operations. This role involves developing a comprehensive security baseline, conducting thorough research on threats, and implementing tools to ensure the security of MLOps pipelines. With a focus on quality and adaptability, you'll work to create a robust validation mechanism for remediation tasks. This position offers the flexibility of remote work with occasional on-site visits, making it ideal for those looking to make a significant impact in the field of security engineering. If you have a passion for machine learning and security, this opportunity is perfect for you.

Qualifications

• 4+ years of experience in Machine Learning and security operations.
• Strong communication skills and previous Federal Government experience preferred.

Responsibilities

• Develop MLOps Security Baseline and conduct research on threats.
• Implement tools for continuous assessment of security in MLOps pipeline.

Skills

Machine Learning

Security Operations

Research on Threats

Communication Skills

Government Policy Knowledge

Education

BS/BA in Computer Science

BS/BA in Information Systems

BS/BA in Software Engineering

Tools

MLOps Tools

Data Analytics Tools

Job description

Summary of Position

SiloSmashers is looking for a Security Engineer to serve as principal security advisor on machine learning security operations (MLSecOps) to support CISA as their MLSecOps program matures.

Principal Duties and Responsibilities

1. Develop MLOps Security Baseline which includes:
1. Conducting thorough research on existing and emerging threats.
2. Use findings from research, incorporating existing Government policy, such as DHS, CISA and NIST, and industry best practice to formulate a presentation of a well-defined security baseline objective which will be Minimal Viable Product (MVP 1).
3. Establish and execute a systematic and quality-focused process for the periodic reassessment and refinement of the security baseline every 90 days to ensure ongoing effectiveness and adaptability to evolving threats in a MLOps pipeline, big data, and analytics environments.
4. Implement a robust tool or process to continuously assess the enterprise environment.
5. Generate regular as-is snapshots (MVP 2) ensuring the highest standards of quality in data accuracy, comprehensiveness, and relevance for effective monitoring of the MLOps pipeline, big data, and analytics infrastructure.
6. Develop a comprehensive tool or process that systematically compares the Minimum Viable Product (MVP, versions 1 and 2) within the MLOps pipeline, big data, and analytics systems, with the aim of identifying gaps and generating a precise list of remediation tasks.
7. Document how the tool or process produces high quality, accurately detecting and categorizing discrepancies between MVP1 and MVP2.
8. Establish a robust validation mechanism to effectively assess the efficacy of the generated remediation tasks in mitigating the identified issues, ensuring the overall security posture of our systems.

Required Skills, Knowledge and Experience

1. BS/BA in Computer Science, Information Systems, Software Engineering or other related analytical, scientific or technical discipline.
2. 4+ years of Machine Learning experience.
3. Effective written and oral communication skills.
4. Previous Federal Government experience is a plus.

Security Clearance

1. Minimum Secret

Work Location

1. 100% remote with occasional on-site visits as needed.