Position Details
About this role
This role focuses on building and deploying production AI capabilities, especially foundation models and large language model systems. You will optimize LLM performance, implement guardrails and evaluation, and help shape the long-term technical vision for foundational AI systems.
Key Responsibilities
- Partner with cross-functional teams to deliver AI-powered products
- Design, develop, test, deploy, and support AI software components
- Leverage AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch
- Invent state-of-the-art LLM optimization techniques
- Contribute to technical vision and long term roadmap
Technical Overview
You will design and operate AI software components spanning foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The work uses AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch, with a focus on LLM optimization for scalability, cost, latency, and throughput.
Ideal Candidate
The ideal candidate is a senior AI engineer focused on production large language model systems, including foundation model training and large language model inference. They bring hands-on experience with guardrails, model evaluation, experimentation, governance, and observability, and they are strong in LLM optimization for scalability, cost, latency, and throughput.
Must-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Must be able to design, develop, test, deploy, and support AI software components including foundation model training and large language model inference, Must have experience with LLM optimization to improve scalability, cost, latency, and throughput
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