AI Engineer: Production-Ready AI Systems

Innovaccer; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Generous PTO benefits

Parental Leave

Rewards & Recognition

Insurance Benefits

Job summary

Innovaccer in San Francisco is seeking an AI Engineer to build production-grade AI systems, including LLM-based solutions, RAG, and automation workflows. You will partner with product, engineering and data teams to design, develop, and deploy AI-powered applications.

The role spans the full lifecycle from experimentation to deployment, requiring hands-on Python and PyTorch, model orchestration, and collaboration with clinicians and operators to ensure reliable outputs.

Qualifications

• MS or PhD in CS/ML; exceptional BS with research considered.
• First-author publications at NeurIPS/ICML/ICLR/ACL/EMNLP or similar; meaningful open-source ML contributions.
• You have fine-tuned an open-weight model yourself and can explain why you chose one.
• Strong Python and PyTorch; familiarity with training and serving stacks (HuggingFace, FSDP/DeepSpeed, vLLM or equivalents).
• Exposure to multi-GPU training and sharding strategies; you know why it matters.
• Evidence you can finish things.

Responsibilities

• Take ideas from paper to prototype to production.
• Build the model layer of a real product and manage model composition with product-level accuracy.
• Write real code in Python and PyTorch; optimize training runs.
• Design experiments with hypotheses and ablations; report results honestly.
• Explain work to non-AI stakeholders including clinicians and operators.

Skills

Python

PyTorch

LLM systems

Multi-GPU training

Experimentation

Production deployment

Communication

Education

MS or PhD in Computer Science or ML

BS with research/open-source work

Tools

HuggingFace

DeepSpeed

vLLM

FSDP

PyTorch Lightning

Job description

Innovaccer in San Francisco is seeking an AI Engineer to build production-grade AI systems, including LLM-based solutions, RAG, and automation workflows. You will partner with product, engineering and data teams to design, develop, and deploy AI-powered applications.

The role spans the full lifecycle from experimentation to deployment, requiring hands-on Python and PyTorch, model orchestration, and collaboration with clinicians and operators to ensure reliable outputs.