AI/ML Engineer (Generative AI & LLMs)
Tasks
- Apply guardrails and evaluation
- Build CI/CD pipelines
- Build LLM-powered applications
- Build vector database pipelines
- Deploy ML models to production
- Deploy containerized applications
- Design generative AI models
- Develop Python data processing code
- Develop agentic workflows
- Fine tune and deploy LLM applications
- Implement MLOps pipelines
- Implement rag pipelines
- Integrate LLM solutions via APIs
- Monitor model performance
- Optimize distributed system performance
- Use prompt engineering
Perks/Benefits
Skills/Tech-stack
APIs | Agentic Workflows | Agile | Anthropic Claude | ArgoCD | Azure DevOps | CI/CD | Evaluation | FastAPI | GitLab CI | Google Gemini | Guardrails | Hugging Face | Jenkins | Kubernetes | Langchain | Llama | Llamaindex | MLOps | Mistral | Model Evaluation | Model Monitoring | MongoDB Atlas | NLP | Neo4j | Neural Networks | NumPy | OpenAI | OpenShift | PGVector | Pandas | Pinecone | Prompt engineering | PyTorch | Python | RAG | Retrieval-Augmented Generation | Scikit-learn | Statistical modeling | TensorFlow | Transformers | Vector Databases | Vertex AI
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | ML Engineer
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