Applied AI Engineer
Tasks
- Architect training and inference pipelines
- Build and optimize large language model systems
- Deploy and monitor machine learning models in production
- Design production AI solutions
- Develop retrieval-augmented generation applications
- Establish responsible AI governance and security best practices
- Evaluate emerging AI technologies and frameworks
- Evaluate model performance and quality
- Implement MLOps workflows
- Mentor AI engineers and lead architecture reviews
- Optimize latency scalability and infrastructure utilization
Perks/Benefits
Skills/Tech-stack
AWS | Agentic AI | CI/CD | Cloud platform | Computer Vision | Deep learning | Distributed Training | Docker | Embeddings | Experimentation | Feature Engineering | GPU Optimization | Google Cloud | Google Cloud Platform | JAX | Kubernetes | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Microsoft Azure | Model Monitoring | Model Serving | Natural Language | Natural Language Processing | Prompt engineering | PyTorch | Python | Ray | Retrieval-Augmented Generation | Statistics | TensorFlow | Vector Databases
Education
Roles
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