AI Architect

Position Title: AI/ML Data Professional

Location

Job Type

Mandatory Skills

SQL, Data Science, AI/ML, GenAI, Data Engineering

Optional Skill

Data Modelling

Role & Responsibilities

• Write clean and efficient Python code for AI, ML, and data science applications
• Conduct in-depth analysis of discrete and multivariate datasets
• Leverage and implement pre-trained AI/ML models for real-world problem-solving
• Perform data manipulation, exploration, and transformation
• Debug and resolve issues in AI pipelines with minimal external assistance
• Apply AI/ML techniques to practical business problems and real-world datasets
• Contribute to AI use cases development, model fine-tuning, and optimization
• Participate in architecture or engineering-specific tasks depending on the applied role
• Demonstrate strong problem-solving skills and the ability to troubleshoot without trivial search dependency

Python Proficiency Requirements

• High speed and accuracy in coding
• Solid understanding of Python syntax, structures, and debugging practices
• Ability to independently solve complex problems using Python
• Familiarity with core libraries like pandas, NumPy, scikit-learn, etc.

AI & Data Analysis Skills

• Strong hands-on expertise in data manipulation and statistical analysis
• Understanding of AI/ML model building, evaluation, and deployment
• Comfortable working with structured and unstructured data
• Experience applying models to real-world business scenarios

Problem-Solving & Debugging

• Ability to read and analyze logs to identify and fix issues
• Logical and structured approach to troubleshooting
• Minimal reliance on basic Google queries to resolve errors

Practical Applications & Use Cases

• Experience applying AI/ML solutions to production-grade datasets
• Effectively use and modify pre-trained models to meet specific objectives
• Ability to connect models to meaningful business outcomes

Interview Task

• Dataset-Based Task

  : Perform multivariate analysis

• Modeling Task

  : Use pre-trained models to implement predictive or classification solutions

• Debugging Task

  : Analyze and fix broken code snippets

• Live Coding Assessment

  : Open-book format; Google is allowed but should not be used for basic algorithm solutions

Role-Specific Focus

• AI Architect Applicants

  : Will be assessed on AI/ML depth, model design, and real-world use case implementation

• Data Engineer Applicants

  : Will be evaluated on data transformation, data pipeline construction, and backend data handling