AI Engineer
Tasks
- Build agentic RAG pipelines
- Containerize applications with Docker and Kubernetes
- Create scalable data ingestion and labeling pipelines
- Design agentic GenAI applications
- Fine-tune and deploy open-source LLMs
- Implement function-calling workflows
- Manage vector databases and embeddings
- Monitor model performance and compliance
- Optimize latency drift bias and security
- Translate requirements into agentic GenAI solutions
Perks/Benefits
- Certification assistance
- Internal Training Portal
- Mentor program
- Tuition assistance
- Wellness program
Skills/Tech-stack
CI/CD | Data labeling | Docker | Feature Engineering | Function Calling | Hugging Face | Instruction Tuning | Kubeflow | Kubernetes | Langchain | Langgraph | LoRA | MLOps | MLflow | PEFT | PyTorch | Python | QLoRA | RAG | RLHF | Retrieval-Augmented Generation | TensorFlow | Vector Databases | Vectorization
Education
Roles
AI | AI Engineer | Engineer
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