Product Intelligence Engineer

1 мес. назад

СШАOnsite

llmvlmphysics-informed modelsscientific codedata servicesmodel routingretrieval

Build AI-powered intelligence products integrating physics-informed models and ultraspectral data for operational decision-making.

О компании

Welcome to Matter, where we are building the future of vision AI: pairing a world-first sensor that sees molecular chemistry, temperature, and 3D shape with a Large World Model that will be the most powerful intelligence engine for the physical world. This system doesn't just see what something looks like; it understands everything from a single pixel. We call this Superintelligent Vision.
Our team has delivered technologies to Mars for NASA/JPL, designed advanced sensors for U.S. Defense, and built core infrastructure at OpenAI. We are now building the next generation of space- and airborne-based sensing systems.

Обязанности

Matter is hiring a Product Intelligence Engineer to turn physics-informed models, general-purpose AI, and ultraspectral data into secure, evidence-backed intelligence products. Reporting to Ignacio Cases Martin, this hands-on individual contributor will build agentic workflows, retrieval and tool integrations, reports, and human-in-the-loop experiences that help customers make operational decisions.
Build production workflows that combine physics-informed models, LLMs, VLMs, world models, scientific code, data services, and deterministic rules through stable interfaces.
Design durable execution across state, planning, model routing, retrieval, memory, tool use, retries, timeouts, checkpoints, human approval, and recovery.
Create evidence-backed outputs that distinguish source data, model inference, system-generated synthesis, user input, and unresolved uncertainty.
Partner with product and design to build workflows for review, correction, comparison, approval, reporting, and recovery.
Build context, retrieval, memory, and indexing patterns that respect permissions, freshness, versioning, retention, and evidence lineage.
Evaluate real system behavior across task success, groundedness, scientific validity, safety, latency, cost, and human intervention.
Customers receive timely, evidence-backed answers and workflows that support real operational decisions.
Agentic capabilities behave predictably across failures, version changes, unavailable dependencies, and human-review boundaries.
Reusable product-intelligence components reduce one-off integration work without obscuring user control or scientific evidence.

Требования

To comply with U.S. export regulations, applicants must be one of the following:
A U.S. citizen or national
A lawful permanent resident (green card holder)
Eligible to obtain required authorizations from the U.S. Department of State

Будет плюсом

Experience with scientific, geospatial, industrial, defense, autonomy, or other high-consequence intelligence systems.
Experience building multimodal applications that combine imagery, maps, time series, documents, structured data, or sensor streams.
Experience with agent evaluation, constrained generation, program synthesis, durable workflow systems, or mixed cloud and edge architectures.
Experience working closely with product and design teams to ship customer-facing capabilities.

Условия

This role is based in El Segundo, CA, and requires onsite work.
At Matter, we believe in rewarding high performance and providing the support you need to thrive. Our compensation and benefits package includes:
Competitive compensation based on experience
Early-stage equity package
100% employer-paid health, dental, and vision coverage
Opportunity to work on novel sensing, data, and AI systems with real-world deployment paths to the largest industries in the world

Другое

Experience building production AI applications, agent systems, workflow engines, backend services, or complex software products.
Strong hands-on engineering skills across APIs, stateful services, databases, asynchronous execution, testing, debugging, and production operation.
Practical experience with LLMs or multimodal systems, retrieval, memory, tool use, model routing, structured generation, and common failure modes.
Product judgment and the ability to connect technical design choices to the user decision or workflow being improved.
Experience building systems with security, permissions, data isolation, auditability, or human-approval requirements.