
AI/ML Developer
7 days ago
Primary Skillset (Core Technical Skills)
These are essential for building, training, and deploying AI/ML models:
Programming Languages
Python (most widely used)
Node.JS, Java (depending on the use case)
Mathematics & Statistics
Linear algebra
- Probability & statistics
Calculus (especially for optimization)
Machine Learning Algorithms
Supervised, unsupervised, and reinforcement learning
- Decision trees, SVMs, k-NN, ensemble methods
Deep learning (CNNs, RNNs, Transformers)
Data Handling & Processing
Data cleaning, transformation, and feature engineering
Libraries: Pandas, NumPy, Scikit-learn
Deep Learning Frameworks
TensorFlow, PyTorch, Keras
Model Deployment & MLOps
Docker, Kubernetes
- MLflow, Airflow
REST APIs (Flask, FastAPI)
Cloud Platforms
AWS, Azure, Google Cloud (for scalable model training and deployment)
Version Control
Git/GitHub for collaboration and code management
Secondary Skillset (Complementary & Soft Skills)
These enhance productivity, collaboration, and problem-solving:
Data Visualization
Tools: Matplotlib, Seaborn, Plotly, Tableau
Communicating insights effectively
Software Engineering Practices
Writing clean, modular, and testable code
Understanding of CI/CD pipelines
Communication Skills
Explaining complex models to non-technical stakeholders
Writing documentation and reports
Research & Continuous Learning
Reading academic papers
Staying updated with latest trends (e.g., LLMs, generative AI)
Ethics & Responsible AI
Bias detection and mitigation
- Fairness, transparency, and accountability in AI systems
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