Applied AI Engineer
Tasks
- Build AI features end-to-end
- Convert model outputs to structured behaviors
- Debug model orchestration and production issues
- Design prompts and agent workflows
- Develop evaluation frameworks for real world performance
- Implement tools and memory systems
- Maintain data pipelines and training loops
- Optimize latency and cost
- Serve and run LLM inference systems
Perks/Benefits
- N/A
Skills/Tech-stack
Agent workflows | Deep learning | Inference | JAX | LLM orchestration | Language Models | Large Language Models | Machine Learning | Model Serving | Prompt engineering | PyTorch | Python | VLLM | Vector Databases
Education
N/A
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