Ingénieur IA (H/f)
Tasks
- Build LLM applications
- Build ML pipelines
- Build vector store retrieval pipelines
- Coordinate with data engineering
- Coordinate with product teams
- Coordinate with software teams
- Deploy LLM microservices
- Deploy machine learning models
- Design machine learning models
- Develop LangChain agents
- Develop LangGraph agents
- Develop RAG architectures
- Evaluate ML models
- Implement CI/CD for ML pipelines
- Implement FastAPI APIs
- Implement Flask APIs
- Implement batching
- Implement chunking strategy
- Implement retrieval-augmented generation
- Ingest documents for RAG
- Manage GPU utilization
- Monitor ML models
- Monitor data drift
- Monitor model drift
- Optimize machine learning models
- Optimize model inference performance
- Parallelize inference
- Reduce inference latency
- Train machine learning models
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Airflow | Amazon Bedrock | Azure | Azure DevOps | Azure OpenAI | CI/CD | Chroma | DVC | Deep learning | Docker | Embeddings | Faiss | FastAPI | Flask | GPU Optimization | GitHub Actions | GitLab | Google Cloud | Huggingface | Kubernetes | LLM | Langchain | Langgraph | Language Models | Language Processing | Large Language Models | Llamaindex | MLflow | Machine Learning | Milvus | NLP | Natural Language | Natural Language Processing | Prefect | PyTorch | Python | Quantization | RAG | REST API | Retrieval-Augmented Generation | TensorFlow | Transformers | VLLM | Vector Database | Vertex AI | Weights and Biases
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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