Senior MLSecOps Engineer

ADP-posted 3 months ago
$79,800 - $213,930/Yr
Full-time • Senior
Hybrid • Roseland, NJ
Professional, Scientific, and Technical Services
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ADP is hiring a Sr. Machine Learning Security Operations (MLSecOps) Engineer. This Hybrid role can sit in Roseland, NJ or Alpharetta, GA. Unlock Your Career Potential: Global Security Organization at ADP. Do you have a passion for going on the offensive to safeguard critical information? As ADP's Global Security Organization (GSO), we know that our clients rely on us for human capital management solutions, but beyond that, they entrust us with one of their most valuable assets — their employee data. We are honored by this trust and are laser focused on securing data at every step in the information lifecycle, ensuring integrity, confidentiality and compliance with industry and government regulations at all times. From the cloud to the data center and across every emerging device, you'll join a team of experts in the GSO who are always staying one step ahead in this ever-changing world of data by continually evolving our strategies and technologies to protect ADP and our clients.

  • Design, implement, and maintain secure ML pipelines for model evaluation, validation, deployment, and inference.
  • Assess and mitigate security risks throughout the ML lifecycle, including data ingestion, model storage, and deployment.
  • Develop and maintain code for ML pipelines using Python and CICD, ensuring robust security controls and compliance with best practices.
  • Institutionalize security scanning of AI/ML models in line with shift left strategy; interpret results and remediate identified issues.
  • Evaluate and optimize model inference deployment strategies, balancing security, performance, and resource utilization.
  • Monitor and secure both structured and unstructured data storage systems used in ML workflows.
  • Stay current on top vulnerabilities affecting Machine Learning Models, Large Language Models (LLMs), and AI agents, such as prompt injection, data poisoning, model theft, and adversarial attacks.
  • Collaborate with data scientists, ML engineers, and security teams to drive adoption of secure ML practices.
  • Build a solution to generate Machine Learning Bill of Materials (AIBoM).
  • Establish strong partnership with key stakeholders in technology and product organizations.
  • Perform other duties as required.
  • Hands-on experience with MLOps pipelines and model deployment tools (e.g., Kubeflow, MLflow, SageMaker).
  • Strong programming skills in Python and CICD for automation and pipeline development.
  • Deep understanding of ML model training and inference algorithms, including their security implications.
  • Familiarity with structured (SQL, data warehouses) and unstructured (object storage, NoSQL) data systems.
  • Familiarity with Databricks.
  • Experience with ML security tools for model scanning and vulnerability assessment.
  • Knowledge of top OWASP AI/ML vulnerabilities, including: Prompt injection, Data and model poisoning, Model extraction and inversion, Adversarial example attacks, Supply chain risks in ML components.
  • Strong communication skills and ability to document and explain Cybersecurity and AI/ML security controls to technical and non-technical stakeholders.
  • Understanding of AL/ML model formats such as pickle, tensorflow, safetensors.
  • Experience in rolling out model scanning solution as part of model development.
  • Understanding CI/CD pipelines covering source control, integration, and deployment (ex: Bitbucket, Jenkins, Rally, JIRA, Artifactory, Nexus, SonarQube, git, Snyk).
  • Previous software engineering/architecture experience (Java, C#, .Net, JavaScript, Python) preferred.
  • Strong analytical/problem solving skills and cross functional knowledge across multiple development and security disciplines.
  • Experience with development of RESTful web services preferred.
  • Understanding of advanced iterative Agile, Cloud and Container Security, GenAI Security.
  • CEH, CISSP, CSSLP, GCIA, GPEN, GWAPT.
  • Medical, Dental, Vision, Life Insurance.
  • Matched Retirement Savings.
  • Wellness Program.
  • Short-and Long-Term Disability.
  • Charitable Contribution Match.
  • Holidays, Personal Days & Vacation.
  • Paid Volunteer Time Off.
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