Senior AI Engineer: Build Production-Grade LLM Solutions

Innovaccer Inc.; San Francisco, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Generous PTO: 20 days per year

Parental Leave

Rewards & Recognition program

Medical, dental, vision; disability &

Job summary

Innovaccer is seeking a Senior AI Engineer to join our AI team in San Francisco and build production-grade AI systems that solve complex problems at scale. You will work with product, engineering, and data teams to design, develop, and deploy AI-powered applications, including LLM-based solutions, AI agents, RAG, and intelligent automation workflows.

The ideal candidate is hands-on, curious, and comfortable across the full AI development lifecycle—from experimentation to production deployment

Qualifications

• MS or PhD in Computer Science, Machine Learning, or related field; exceptional BS with OSS considered.
• First-author NeurIPS/ICML/ICLR/ACL/EMNLP publications or strong OSS contributions; AI lab internship.

Responsibilities

• Take ideas from paper to prototype to production; stretch across the full lifecycle.
• Build model layer of a real product, selecting models and composing systems.
• Write real code in Python and PyTorch; optimize training performance.
• Design experiments with hypotheses, ablations, and clear results.
• Explain work to clinicians and operators to ensure correct outcomes.

Skills

Experiment design

Mentoring

Plan scoping

Production mindset

Communication

Research-to-prod translation

Education

MS/PhD in CS/ML

Exceptional BS with OSS

Tools

Python

PyTorch

HuggingFace

DeepSpeed

vLLM

SGLang

FSDP

Multi-GPU training

Job description

Innovaccer is seeking a Senior AI Engineer to join our AI team in San Francisco and build production-grade AI systems that solve complex problems at scale. You will work with product, engineering, and data teams to design, develop, and deploy AI-powered applications, including LLM-based solutions, AI agents, RAG, and intelligent automation workflows.

The ideal candidate is hands-on, curious, and comfortable across the full AI development lifecycle—from experimentation to production deployment