Applied AI Engineer
Tasks
- Architect training and inference pipelines
- Build and fine-tune large language models
- Deploy and monitor production machine learning models
- Design and deploy production AI and machine learning solutions
- Develop RAG systems with vector databases
- Establish model evaluation and responsible AI practices
- Evaluate emerging AI technologies and frameworks
- Implement NLP and computer vision machine learning pipelines
- Mentor AI engineers and lead technical architecture reviews
- Optimize model performance and latency
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 | NLP | Natural Language | Natural Language Processing | Prompt engineering | PyTorch | Python | Ray | Retrieval-Augmented Generation | Statistics | TensorFlow | Vector Databases
Education
Roles
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