Position Title: AI/ML Data Professional
Location: Remote
Job Type: Full-Time / Contract
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
