AI/ML Architect

Job Description       

Technical/Functional Skills:-       
• Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
• Experienced AI Architect with 10+ years of experience in architecting, designing and deploying Machine Learning (ML) solutions to generate business value
• Proven track record of  providing solutions from initiation stage to Production deployment.
• Solid theoretical and practical knowledge of some or most 
o Econometric/statistical methods like Linear Regression, Logistic regression, Generalized Linear Model, Survival Analysis, Sampling Techniques, Time Series Analysis, CART, CHAID, Clustering, Discriminant Analysis, Principal Component Analysis, Factor Analysis, Multidimensional Scaling etc.
o Machine Learning techniques like Random Forest, Support Vector Machine, Gradient Boosting Machine, XG Boost etc.
o Deep Learning techniques across Recurrent Neural Networks, Convolutional Neural Networks etc. and Transformer Architectures as applied in the domains of Natural Language Processing (NLP) and / or Computer Vision (CV)Consistent track record of building and successfully deploying Machine Learning solutions with demonstrable value to the organization
o Generative AI techniques like RAG, Agentic Workflows, Graph RAG, Model Tuning etc.
• Data Preprocessing, Feature Engineering, Data Visualization, Exploratory Data Analysis (EDA), Statistical Analysis
• Extensive experience in Cloud security, MLOps
• Excellent analytical and problem-solving skills, with the ability to translate complex business requirements into technical solutions.
• Strong communication and interpersonal skills to effectively collaborate with technical and non-technical stakeholders.
• Previous experience in mentoring or leading technical teams.
• Familiarity with security and compliance considerations related to automation solutions.
• Extensive knowledge of automation technologies, AI/ML, cloud computing

 

Experience Required:-    Yes
Roles & Responsibilities:-
• Operationalizing AI, mapping requirements to implementation, selecting the appropriate technologies, and evaluating non-functional attributes such as security, usability, and stability. 
• AI Architect closes this data-to-insight-to-action loop, which requires deep understanding of the applications and integration infrastructure environment. Setting up AI/ML processing environments in IT landscape is a must. 
• Detailing mapping IT and security process to AI process. Influencing and working with business partners to establish and accelerate AI adoption. Audit AI solutions for architecture, scalability and security; especially in an enterprise landscape with cloud as apriority. 
• Mapping requirements to implementation - Analyzing, coordinating, prioritizing and optimizing requirements. Ensuring implementation even with constraints. 
• Selecting technology - selecting appropriate technologies from the many open source, commercial on-premises, and cloud-based offerings available. Integrating a new generation of tools within the existing environment is also to help ensure access to accurate and current data. Because technology in this domain is evolving rapidly, 
• Ensures that components can be replaced with well-suited alternatives that do not require any adjustment or downtime. 
• Foresight when selecting new technologies like Functional and non functional requirements - considering aspects like security, usability and stability.

 

Preferred Skills:-
• Previous involvement in large-scale organizations implementing automation strategies.
• Proficiency AI/ML technologies.
• Domain Driven Design experience
• Ability to work on multiple large-scale technology initiatives concurrently?€? 
• Exceptional interpersonal skills in areas such as teamwork, facilitation and negotiation 
• Excellent analytical and collaboration skills and techniques to create innovative market leading solutions 
• Excellent time management, communication, decision making and presentation skills 
• Global team experience 


Qualification:- BACHELOR OF COMPUTER SCIENCE