AI-ML Engineer II
INR 3000K-5000K (estimate) Senior-level Full Time
Tasks
- Architect and improve retrieval augmented generation systems
- Build and harden MLOps and LLMOps pipelines
- Create technical documentation and deployment artifacts
- Define prompt engineering standards and evaluation frameworks
- Design and build agentic AI and multi agent workflows
- Develop fine tune and optimize ML and LLM pipelines
- Drive engineering quality through code and design reviews
- Evaluate emerging models and pilot for enterprise use
- Implement LLM guardrails for safe high quality systems
- Integrate enterprise applications and APIs with data platforms and vector stores
- Lead technical design and delivery of machine learning and generative AI components
- Mentor junior engineers and contribute to reusable frameworks
Perks/Benefits
Skills/Tech-stack
AWS | Agent systems | Agentic AI | Airflow | Autogen | Azure | CI/CD | Chunking | Containerization | CrewAI | Docker | Drift Detection | Fine Tuning | Generative AI | Google Cloud | Guardrails | Hugging Face | Hybrid retrieval | Kubernetes | LLM Pipelines | LLMOps | Langchain | Langgraph | Language Models | Large Language Models | LoRA | MLOps | Machine Learning | Model Drift | Model Drift Detection | Model Evaluation | Model Monitoring | Multi-Agent | Multi-Agent Systems | Observability | PEFT | Prompt engineering | PyTorch | Python | RAG | Ray | Re-ranking | Retraining | Retrieval-Augmented Generation | TGI | TensorFlow | Triton | VLLM | Vector Databases
Education
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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