AI Foundational Model Engineer
Tasks
- Build retrieval-augmented generation pipelines
- Create production documentation runbooks and audit records
- Deploy and optimize production AI services
- Design and build foundation model applications
- Embed security privacy and responsible AI controls
- Implement LLMOps and MLOps lifecycle
- Implement prompt retrieval and service observability
- Integrate AI services with AWS hosted platform components
- Monitor evaluate and rollback model services
- Optimize inference latency throughput token efficiency and cost
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | AWS Bedrock | AWS ECS | AWS EKS | AWS Lambda | Amazon SageMaker | Azure OpenAI | CI/CD | Data Governance | Docker | Embeddings | Hugging Face | Inference Optimization | Infrastructure as Code | Kafka | Kubeflow | Kubernetes | Langchain | Llamaindex | LoRA | MLflow | Model Evaluation | Model Monitoring | OpenAI | OpenSearch | PEFT | PyTorch | Python | RAG | Reranking | Semantic Search | TensorFlow | Terraform | Transformers | Triton | VLLM | Vector Database | Vertex AI | “as-code”
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
Cities
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