LLM Inference Engineer at Hippocratic AI Palo Alto, CA

Hippocratic AI is building safety-focused large language model (LLM) for the healthcare industry. Our team comprised of ex-researchers from Microsoft, Meta, Nvidia, Apple, Stanford, John Hopkins and Hugging Face are reinventing the next generation of foundation model training and alignment to create AI-powered conversational agents for real time patient-AI interactions.

We're seeking an experienced LLM Inference Engineer to optimize our large language model (LLM) serving infrastructure. The ideal candidate has:

• Extensive hands-on experience with state-of-the-art inference optimization techniques

• A track record of deploying efficient, scalable LLM systems in production environments

• Design and implement multi-node serving architectures for distributed LLM inference

• Optimize multi-LoRA serving systems

• Apply advanced quantization techniques (FP4/FP6) to reduce model footprint while preserving quality

• Implement speculative decoding and other latency optimization strategies

• Develop disaggregated serving solutions with optimized caching strategies for prefill and decoding phases

• Continuously benchmark and improve system performance across various deployment scenarios and GPU types

• 2+ years of experience optimizing LLM inference systems at scale

• Proven expertise with distributed serving architectures for large language models

• Hands-on experience implementing quantization techniques for transformer models

• Strong understanding of modern inference optimization methods, including:

• Proficiency in Python and C++

• Experience with CUDA programming and GPU optimization (familiarity required, expert-level not necessary)

• Contributions to open-source inference frameworks such as vLLM, SGLang, or TensorRT-LLM

• Experience with custom CUDA kernels

• Track record of deploying inference systems in production environments

• Deep understanding of performance optimization systems

Our team is pushing the boundaries of what's possible with LLM deployment. If you're passionate about making state-of-the- art language models more efficient and accessible, we'd love to hear from you!

• Innovative Mission:
  We are developing a safe, healthcare-focused large language model (LLM) designed to revolutionize health outcomes on a global scale.

• Visionary Leadership:
  Hippocratic AI was co-founded by CEO Munjal Shah, alongside a group of physicians, hospital administrators, healthcare professionals, and artificial intelligence researchers from leading institutions, including El Camino Health, Johns Hopkins, Stanford, Microsoft, Google, and NVIDIA.

• Strategic Investors:
  We have raised a total of $278 million in funding, backed by top investors such as Andreessen Horowitz, General Catalyst, Kleiner Perkins, NVIDIA’s NVentures, Premji Invest, SV Angel, and six health systems.

• World-Class Team:
  Our team is composed of leading experts in healthcare and artificial intelligence, ensuring our technology is safe, effective, and capable of delivering meaningful improvements to healthcare delivery and outcomes.

For more information, visit .

We value in-person teamwork and believe the best ideas happen together. Our team is expected to be in the office five days a week in Palo Alto, CA unless explicitly noted otherwise in the job description