
High Salary AI Engineer
7 days ago
Core Responsibilities of an AI Engineer
Must have
- Integrate CI/CD pipelines
- Manage containers (e. g. , Docker, Kubernetes)
- Automate deployment and scaling processes
- Model Development & Deployment: Build scalable AI/ML models for real-world applications, including NLP, computer vision, and GenAI use cases123.
- Data Engineering: Preprocess large-scale structured and unstructured datasets, optimize pipelines, and extract insights7.
- MLOps & Automation: Implement best practices for training, deployment, and monitoring of AI systems using tools like MLflow, Docker, and cloud platforms (AWS, Azure, GCP)4.
Good to have
- Collaboration: Work with cross-functional teams software engineers, data scientists, product managers to integrate AI into products1.
- Research & Innovation: Stay updated with the latest AI trends, research papers, and tools (e. g. , LangChain, RAG, LLMs)5.
- Mentorship: Guide junior engineers and contribute to team development3.
Skills & Qualifications
- Programming: Strong in Python, with experience in TensorFlow, PyTorch, Scikit-learn, and data manipulation libraries (Pandas, NumPy)
- AI Concepts: Deep understanding of supervised/unsupervised learning, NLP, deep learning, and GenAI.
- Tools & Frameworks: Experience with vector databases, containerization, orchestration, and prompt engineering.
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