AI Engineer
Tasks
- Apply responsible AI and AI governance
- Apply safety guardrails and compliance
- Architect multi-agent AI systems
- Benchmark models against performance and safety requirements
- Build Databricks MLflow workflows
- Build production grade Graph RAG systems
- Build production grade RAG systems
- Conduct bias detection and hallucination mitigation
- Design multimodal generative AI pipelines
- Develop Python inference orchestration services
- Engineer agent memory and context management
- Establish LLMOps and MLOps pipelines
- Implement RLHF and PEFT with LoRA
- Implement async job handling and streaming responses
- Implement explainability dashboards
- Integrate vector databases and knowledge graphs
- Lead development of generative AI and ML solutions
- Perform LLM fine tuning and model alignment
- Use regression clustering forecasting and ensemble methods
Perks/Benefits
- N/A
Skills/Tech-stack
API Development | AWS Neptune | AWS SageMaker | Amazon Bedrock | Async Programming | Autogen | Azure OpenAI | CrewAI | Databricks | Deep learning | Embeddings | FastAPI | Feature Store | GCP Vertex | GCP Vertex AI | Gemini | Graph RAG | Hugging Face | Instruction Tuning | Knowledge graphs | LLMOps | Langchain | Langgraph | Language Models | Language Processing | Large Language Models | LoRA | MLOps | MLflow | Machine Learning | Multimodal Learning | Natural Language | Natural Language Processing | Neo4j | OpenAI API | OpenSearch | PEFT | PGVector | Pinecone | Prompt engineering | PyTorch | Python | RAG | RLHF | SQL | Semantic Search | TensorFlow | Transformer Models | Vector Databases | Vertex AI | Weights and Biases
Education
Roles
AI | AI Engineer | Engineer | Lead | Lead AI Engineer
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