Staff Applied AI Engineer

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

Senior Member of Technical Staff (Applied AI)
AI-Powered Pharmaceutical Marketing
New York City (on-site)
$230k – $350k + equity

Join a Series A startup redefining how life sciences organizations commercialize therapeutics. You’ll own the technical direction of the AI systems: retrieval, generation, verification, evaluation, and keeping everything running in production. Every claim in pharma marketing content must trace to an approved source, and building persuasive, defensible content at speed is a genuine hard problem with no playbook. You’ll work directly with the VP of Engineering and co-founders, shaping architecture, product strategy, and technical hiring.

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: prescribing information, clinical data, approved assets, style guides, claim libraries


• Develop offline evaluation metrics that predict downstream MLR review outcomes, where ground truth arrives slowly as inconsistent reviewer redlines


• Connect generated assets to real-world performance: engagement, HCP response, scripts written, and feed that data back into the system


• Run full ML ops: CI/CD for ML, versioning, automated testing, monitoring, and behavioral regression detection


• Ship high-craft output: visual and textual excellence that survives generation without getting quietly rewritten

Requirements

• Deep production experience shipping, operating, and maintaining ML/LLM systems


• Evaluation instinct: a history of inventing metrics to measure and improve systems


• Depth in LLMs: retrieval, agentic pipelines, targeted fine-tuning, and judgment on the right tool for each job


• Full-stack proficiency: Python, FastAPI, Docker, AWS, able to take ideas from research to deployed service independently


• Comfort making confident decisions amid ambiguity and adjusting fast


• Direct, open communication style

Why apply?

• Ground-floor role with real architectural ownership at a fast-growing startup working with 50+ pharma brands


• Hard, unsolved technical problems: provenance-preserving generation, slow-ground-truth evaluation, regulated AI


• Top-tier backing, ground-floor equity, and influence over product and hiring from day one


• Competitive NYC comp, relocation support, visa sponsorship (O-1, H-1B, TN), unlimited PTO, 401(k) with 4% match, in-office lunches