Applied AI Engineer
Tasks
- Architect training inference and MLOps pipelines
- Build Retrieval Augmented Generation systems
- Deploy and monitor production ML models
- Design production AI solutions
- Develop machine learning pipelines
- Ensure responsible AI governance and security
- Fine-tune and evaluate large language models
- Implement NLP computer vision and recommendation models
- Mentor AI engineers and lead architecture reviews
- Optimize model performance, latency, and scalability
Perks/Benefits
Skills/Tech-stack
AWS | CI/CD | Cloud platform | Computer Vision | Deep learning | Distributed Training | Docker | Embeddings | Feature Engineering | GPU Optimization | Google Cloud | Google Cloud Platform | JAX | Kubernetes | Langchain | Langgraph | Language Models | Language Processing | Large Language Models | Llamaindex | MLOps | Machine Learning | Microsoft Azure | Model Monitoring | Model Serving | NLP | Natural Language | Natural Language Processing | Prompt engineering | PyTorch | Python | Ray | Recommendation Systems | Retrieval-Augmented Generation | TensorFlow | Vector Databases
Education
Roles
AI | AI Engineer | Applied AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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