Roles & responsibilities

KPMG Delivery Network (KDN) is seeking a talented DevMLSecOps Manager to lead and implement a holistic approach to developing, securing, and operating our ML systems. You will be pivotal in fostering a culture of security and efficiency throughout the entire ML lifecycle, from data exploration to model deployment and monitoring. This role requires a strong technical foundation in software development, machine learning operations, and security principles, along with team management and collaboration skills.

Key responsibilities include:

1.

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.

2.

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.

3.

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.

4.

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.

Educational qualifications

- Bachelors or Master’s 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

- Solid 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).

📌 DevMLSecOps Manager(AIML-Security) (Karnataka)
🏢 KPMG India
📍 Karnataka