Job
Description
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. Requirements: 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. . Bachelors or Masters degree in Computer Science, Cybersecurity, Information Technology, or related fields. A minimum of 5+ years of hands-on experience in conducting cyber risk assessments and related security assessments. Industry certifications such as CISSP, CCSP, CISA, CISM, CRISC, ISO/IEC:27001/22301/20000 LI/LA or equivalent are highly valued. Profound knowledge of cybersecurity frameworks, industry standards, and best practices. Proficiency in using various security assessment and techniques. Strong analytical and problem-solving skills, with the ability to think critically and strategically. Excellent communication and presentation skills, capable of effectively communicating technical concepts to both technical and non-technical audiences. Demonstrated experience in project management and handling multiple assessments simultaneously. A proactive and self-motivated approach to work, with a commitment to continuous learning and professional development. Network Security, infrastructure assessment and network architecture design review. Conceptual knowledge of OT Security/ISA 62443 standard is preferable.
