AI Engineer (India, China)
Tasks
- Build agentic AI systems
- Build data pipelines for training, evaluation, inference
- Design and deploy machine learning models
- Develop vector database solutions
- Document architectures and technical decisions
- Fine-tune large language models
- Implement MLOps and LLMOps practices
- Implement rag pipelines
- Implement responsible AI guardrails and compliance
- Integrate AI models via APIs microservices or embedded systems
- Orchestrate long running agent workflows
- Perform prompt engineering and structured outputs
- Run experiments and A B tests for quality evaluation
Perks/Benefits
- Annual leave
- Flexible working
- Life insurance
- Medical insurance
- Parental leave
- Retirement savings
- Sabbatical
- Volunteering leave
Skills/Tech-stack
APIs | AWS | Airflow | Apache Spark | Autogen | Azure | Bias Mitigation | CI/CD | CrewAI | Data Privacy | Databricks | Docker | Embeddings | Explainability | Few-Shot Learning | Few-shot | Generative AI | Google Cloud | Kubeflow | Kubernetes | LLMOps | Langchain | Langgraph | Langsmith | Language Models | Large Language Models | Llamaindex | MLOps | MLflow | Machine Learning | Microservices | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | SQL | SageMaker | Security Compliance | Semantic Kernel | Temporal | Vector Databases | Vector Search | Weights and Biases
Roles
AI | AI Engineer | Engineer
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