Talent.com
This job offer is not available in your country.
DevSecOps Engineer - Machine Learning System

DevSecOps Engineer - Machine Learning System

td newton and associatesGurugram
25 days ago
Job description

Key responsibilities include :

Integrated Development and Security for ML Systems :

  • Define and implement DevMLSecOps best practices, integrating security seamlessly into the ML development lifecycle
  • Establish secure coding standards and guidelines specific to machine learning pipelines and model development.
  • Design and implement secure and automated CI / CD pipelines for ML models, incorporating security gates and testing at each stage.
  • Collaborate with Data Scientists and ML Engineers to build secure and robust ML applications and services.

Secure ML Infrastructure and Deployment :

  • Architect and maintain secure and scalable infrastructure for training, deploying, and monitoring machine learning models, leveraging cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
  • Implement robust security controls for ML components.
  • Ensure secure deployment and management of ML models in production environments, including access control, monitoring, and logging.

    • ML Security and Vulnerability Management :

  • Lead threat modeling activities specific to machine learning systems, identifying unique security risks and attack vectors.
  • Implement and manage vulnerability scanning and security testing tools tailored for ML components and infrastructure.
  • Establish processes for secure data handling throughout the ML lifecycle, including data encryption, anonymization, and access controls.
  • Stay current on the latest research and trends in adversarial machine learning and defense mechanisms.

    • Automation, Monitoring, and Incident Response for ML Security :

  • Drive the automation of security tasks within the ML pipeline and infrastructure.
  • Implement comprehensive monitoring and logging for ML systems, including performance metrics, security events, and anomaly detection.
  • Develop and maintain incident response plans specifically for security incidents affecting ML systems
  • Establish key security metrics and dashboards to track the security posture of ML Governance, and Team Enablement :
  • Collaborate closely with data scientists, developers, DevOps, and Security teams to foster a security-first mindset.
  • Define and enforce security policies and governance frameworks specific to machine learning.
  • Drive security training and awareness programs for the AI and development teams on ML-specific security considerations.
  • Evaluate and recommend security tools and technologies relevant to DevMLSecOps.

    • Educational qualifications :

  • Bachelors or Masters degree in Computer Science, Information Security, Machine Learning, or a related field.
  • Relevant security certifications (e.g., CISSP, CCSK, cloud security certifications) are a plus.

    • Work experience :

  • 8+ years of experience in ML development, DevOps, machine learning operations, and security engineering roles.
  • Strong understanding of MLOps security, AI adversarial threats, model poisoning , data exfiltration and AI risk frameworks.
  • Hands-on experience with AI security tools (e.g., ModelScan, RobustML, Microsoft Purview, IBM AI OpenScale).
  • Experience securing ML pipelines, LLMs, and AI APIs.
  • Deep knowledge of cryptographic techniques for AI security (homomorphic encryption, secure multi-party computation, differential privacy, etc.).
  • Familiarity with secure AI coding practices (e.g., Python, TensorFlow, PyTorch, LangChain security best practices).

    • Skills :

  • Strong proficiency in either Azure or GCP and its security services.
  • Hands-on experience with containerization and orchestration technologies (Docker, Kubernetes) and their security best practices.
  • Expertise in implementing and managing CI / CD pipelines, with a focus on integrating security testing and validation.
  • Experience with security tools and technologies relevant to cloud security, application security, and infrastructure security.
  • Scripting and automation skills (e.g., Python, Bash) are essential.
  • Knowledge of data security and privacy regulations (e.g., GDPR, CCPA).

    • ref : hirist.tech)

    Create a job alert for this search

    Machine Learning Engineer • Gurugram