Drimva

SandboxAQ

Principal Product Manager, Material Science

$163K–$306K

United States · Remote · Principal · Full-time · Posted Oct 30, 2026

Experience
5+ years in product management.
Education
Bachelor's degree in Chemistry, Chemical Engineering or Materials Science or equivalent practical experience.

About the job

Own the catalysis product strategy for SandboxAQ’s AI-driven materials discovery platform, delivering government-funded program objectives while building a commercial product business.

What you'll do

  • Set the end-to-end catalysis product strategy and roadmap, including contractual deliverables, scientific capabilities, and commercial expansion.
  • Translate customer and partner needs into prioritized product requirements, and work with scientific and ML teams on datasets, models, and benchmarking.
  • Develop commercialization plans, value propositions, pricing and packaging input, partnerships, and product and revenue KPIs.

What they ask for

  • 5+ years in product management, including ownership of a technically deep product sold to external customers.
  • Strong grounding in materials science, catalysis, chemistry, or chemical engineering.
  • Track record shipping AI/ML-driven scientific or engineering software to external paying or contracted users.
  • Bachelor's degree in Chemistry, Chemical Engineering or Materials Science or equivalent practical experience.

Nice to have

  • Experience in a major catalysis end market or semiconductor/electronic materials process chemistry.
  • Familiarity with computational chemistry workflows such as density functional theory (DFT), molecular dynamics, or microkinetic modelling.

Pay

$163.2K – $306K • Multiple Ranges (currency and whether base salary or total pay not stated)

Tools

Large Quantitative Models (LQMs), AI/ML, density functional theory (DFT), molecular dynamics, microkinetic modelling, multi-tenant SaaS, API

AI focus

Own product development for an AI-driven materials discovery platform, including defining scientific dataset and model requirements, benchmarking, and advancing catalysis modeling toward reaction-level predictions.

Model-written summary · the original posting is authoritative

First seen Oct 31, 2026 · Last verified Nov 4, 2026 (UTC)