Applied Agentic AI Lead, Partner Co-Design

Tasks

• Build RAG inference multi agent and long horizon workflows
• Co design production agentic systems
• Collaborate with product engineering research and solution architecture
• Define technical objectives timelines and adoption strategy
• Develop fine tuning post training and RL workflows
• Drive evaluations of NVIDIA libraries
• Implement reasoning and agent evaluations and observability
• Lead technical engagement for software adoption
• Maintain up to date knowledge of models libraries and frameworks
• Represent partner needs in architecture and roadmap planning
• Research prototype and validate new AI scenarios
• Ship code and reference architectures

Perks/Benefits

• Equity
• Health benefits

Skills/Tech-stack

Agent systems | Compliance | Deep learning | Docker | Dynamo | Efficient Fine Tuning | Fine Tuning | Generative AI | Governance | Human Feedback | Inference | Kubernetes | LLM Evaluation | LLMOps | Langchain | Language Models | Large Language Models | Learning from Human Feedback | MLOps | Machine Learning | Multi-Agent | Multi-Agent Systems | NEMO | Nim | Observability | PEFT | Parameter efficient fine-tuning | Python | RAG | Reasoning | Reinforcement Learning | Reinforcement Learning from Human Feedback | Retrieval-Augmented Generation | SFT | Security | Supervised Fine Tuning | TensorRT-LLM | VLLM | Vector Databases