AI Engineer
Tasks
- Apply statistical and ML models in hybrid architectures
- Architect multi-agent AI systems
- Build RAG and Graph RAG systems
- Develop Python backend services for LLM orchestration
- Develop multimodal generative AI pipelines
- Establish LLMOps and MLOps pipelines
- Implement agent state and context management
- Implement responsible AI and AI governance
- Lead LLM fine tuning and model alignment
- Research evaluate and productionize generative AI systems
Perks/Benefits
- N/A
Skills/Tech-stack
API Development | AWS Bedrock | AWS Neptune | AWS SageMaker | Anthropic | Async Programming | Autogen | Azure OpenAI | CrewAI | Databricks | Deep learning | Embeddings | FastAPI | GCP Vertex | GCP Vertex AI | Gemini | Graph RAG | Hugging Face | Knowledge graphs | Langchain | Langgraph | Language Models | Large Language Models | LoRA | MLflow | Machine Learning | Neo4j | OpenAI | OpenSearch | PEFT | PGVector | Pinecone | Prompt engineering | PyTorch | Python | RLHF | Responsible AI | Retrieval-Augmented Generation | SQL | Semantic Search | TensorFlow | Transformer Models | Vector Databases | Vertex AI | Weights and Biases
Education
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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