AI Engineer
Tasks
- Apply prompt engineering
- Build MLOps CI CD for ML
- Build deployment pipelines
- Build evaluation frameworks
- Build model serving infrastructure
- Create automated testing frameworks
- Deploy models to production
- Design low latency, high throughput systems
- Develop RAG architectures
- Evaluate model accuracy
- Fine-tune language models
- Identify edge cases
- Implement model versioning
- Implement monitoring and observability
- Integrate AI into product
- Own LLM lifecycle end to end
- Prepare data for fine-tuning
- Provision infrastructure with Terraform
- Use vector databases
- Work on embedding models
Perks/Benefits
Skills/Tech-stack
AWS | Automated testing | CI/CD | Deployment Pipelines | Embedding Models | Fine Tuning | High Throughput | High-Throughput Systems | Keras | Language Models | Large Language Models | Low Latency | Low-Latency Systems | MLOps | Model Monitoring | Model Serving | Model versioning | Observability | Prompt engineering | PyTorch | Python | RAG | TensorFlow | Terraform | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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