Senior Applied AI Engineer - Pharma Marketing, NYC On-site

Storm3; New York (NY); On-site; USD 230,000 - 350,000; Full time

Benefits offered by this job

Relocation support

Visa sponsorship

Unlimited PTO

401(k) with match

In-office lunches

Job summary

Storm3 in New York City is seeking a Senior Member of Technical Staff (Applied AI) to own the technical direction of AI systems for pharma marketing. You will lead retrieval, generation, verification, evaluation, and production readiness, working with the VP of Engineering and co-founders to shape architecture and hiring.

Expect to drive end-to-end ML systems, establish metrics, ensure compliant provenance, and deliver persuasive, defensible content at speed in a fast-growing startup.

Qualifications

• Deep production experience shipping, operating, and maintaining ML/LLM systems.
• History of inventing metrics to measure and improve systems.
• Expertise in retrieval, agentic pipelines, and fine-tuning for LLMs.
• Direct, open communication style and ability to work independently.

Responsibilities

• Own retrieval, generation, verification, and evaluation for AI-generated pharma marketing assets: emails, banners, slides, leave-behinds.
• Build claim-level attribution so every sentence traces back to a specific, defensible source across proprietary corpora.
• Develop offline evaluation metrics that predict downstream MLR review outcomes.
• Connect generated assets to real-world performance: engagement, HCP response, scripts, and data feedback.
• Run full ML ops: CI/CD for ML, versioning, automated testing, monitoring, and regression detection.
• Ship high-craft output: visually and textually excellent content that survives generation.

Skills

ML/LLM systems

Evaluation metrics

LLM retrieval & pipelines

Ambiguity tolerance

Communication

Tools

Python

FastAPI

Docker

AWS

Job description

Storm3 in New York City is seeking a Senior Member of Technical Staff (Applied AI) to own the technical direction of AI systems for pharma marketing. You will lead retrieval, generation, verification, evaluation, and production readiness, working with the VP of Engineering and co-founders to shape architecture and hiring.

Expect to drive end-to-end ML systems, establish metrics, ensure compliant provenance, and deliver persuasive, defensible content at speed in a fast-growing startup.