Senior - CloudSec
About KPMG in India
KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada.
KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment.
We are seeking a highly skilled and knowledgeable AI Consultant to join our information/cyber security team. The ideal candidate should have a deep understanding of both information security principles and the unique challenges that AI/ML technologies present. This role involves ensuring AI systems are fair, transparent, and robust, while mitigating potential risks associated with AI technologies.
Responsibilities:
Develop and implement machine learning algorithms for various projects, with a focus on the financial and banking domain.
Utilize expertise in bias and variance algorithms to enhance model accuracy and performance
Develop and apply techniques for Explainability, Privacy, and fairness in AI models and Generative AI.
Use case development including building AI applications, such as Deep learning, LLM/RAG/finetuning, NLP, computer vision and pattern recognition.
Design and implement cloud solutions, build MLOps Pipeline on cloud (AWS, Azure, or GCP) and on-prem setup along with CI/CD Pipelines.
Design and develop NLP-based applications and system using DL, neural networks and chatbots or AI agents.
Work with data mining toolkits like NLP, Semantic Web, NLTK, and information retrieval libraries like Lucene, SOLR.
Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Circle CI, Airflow or similar tools
Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, Testing and Automation and monitoring of Model's quality
Deploy the Responsible AI technical framework to Cloud.
Build and maintain databases such as NoSQL dbs, Vector Dbs, and object storages.
Identify ways of embedding AI/ML services into enterprise architecture seamlessly.
Keep abreast of the latest AI/ML threats, vulnerabilities, and countermeasures.
Monitor and evaluate model performance, making necessary adjustments to improve accuracy and efficiency.
Communicate with a team of data scientists, data engineers and architect, document the processes
Stay up to date on emerging AI technologies, framework and methodologies.
Requirements:
3-5 years of hands-on experience in software development, with a focus on AI/ML, NLP, DL.
Strong knowledge of AI/ML algorithms, Recommendation systems, Reinforcement Learning, Gen AI and AI Agents.
Proficient in any one of the programming languages like Python or R, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc., with a strong understanding of AI compliance.
Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure or GCP/On-premise hosting) .
Well-versed with various AI/ML libraries for managing Bias, Variance etc.
Experience in FastAPI.
Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes, OpenShift
Having knowledge or an understanding of Open Source Tools such as MLFlow and Fairlearn.
Having an understanding of Gen AI prompt engineering techniques such as N-Shot, Chain of thoughts, Cove, etc.
Ability to stay updated with the latest AI/ML security trends and technologies.
| Equal employment opportunity information KPMG India has a policy of providing equal opportunity for all applicants and employees regardless of their color, caste, religion, age, sex/gender, national origin, citizenship, sexual orientation, gender identity or expression, disability or other legally protected status. KPMG India values diversity and we request you to submit the details below to support us in our endeavor for diversity. Providing the below information is voluntary and refusal to submit such information will not be prejudicial to you. |
Bachelor'sdegree in computer science or software engineering
Strong experience with AI/ML,Gen AI, Agentic AI, Responsible AI, MLOps & cloud.
Preferred tohave any associated Cloud, AI/ML, responsible AI Certification
1-3 years of hands-on experience in software development, with a focus on AI/ML, NLP, DL.
Strong knowledge of AI/ML algorithms, Recommendation systems, Reinforcement Learning, Gen AI and AI Agents.
Proficient in any one of the programming languages like Python or R, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc., with an understanding of AI compliance.
Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure or GCP/On-premise hosting).
Well-versed with various AI/ML libraries for managing Bias, Variance etc.
Experience in FastAPI.
Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes, OpenShift
Having knowledge or an understanding of Open Source Tools such as MLFlow and Fairlearn.
Having an understanding of Gen AI prompt engineering techniques such as N-Shot, Chain of thoughts, Cove, etc.
Ability to stay updated with the latest AI/ML security trends and technologies.
Equal employment opportunity information
KPMG India has a policy of providing equal opportunity for all applicants and employees regardless of their color, caste, religion, age, sex/gender, national origin, citizenship, sexual orientation, gender identity or expression, disability or other legally protected status. KPMG India values diversity and we request you to submit the details below to support us in our endeavor for diversity. Providing the below information is voluntary and refusal to submit such information will not be prejudicial to you.
Develop and implement machine learning algorithms, Generative AI models for various projects, with a focus on the financial and banking domain.
Develop and apply techniques for Explainability, Privacy, and fairness in AI models and Generative AI.
Use case development including building AI applications, such as Deep learning, LLM/RAG/finetuning, NLP, computer vision and pattern recognition.
Work with a team of AI/ML engineers and data scientist to implement AI solutions, or AI agents, build MLOps Pipeline on cloud (AWS, Azure, or GCP) and on-prem setup along with CI/CD Pipelines.
Work with data mining toolkits like NLP, Semantic Web, NLTK, and information retrieval libraries like Lucene, SOLR, Elastic.
Work with version controls such as Git or bitbucket.
Work with containerization and docker implementation and Kubernetes
Optimize Gen AI models for improved accuracy.
Testing and monitoring the AI models for accuracy and efficiency.
Keep abreast of the latest AI/ML threats, vulnerabilities, and countermeasures.
Communicate with a team and document the processes
Stay up to date on emerging AI technologies, framework and methodologies.
