Applied AI Engineer (Product)
About The Position
Matter is building the future of vision AI with a unique sensor and a Large World Model to create Superintelligent Vision. This system understands more than just appearance, analyzing molecular chemistry, temperature, and 3D shape from a single pixel. The team has a strong background in advanced technologies, including work for NASA/JPL and OpenAI. This role focuses on turning physics-informed models, general-purpose AI, and ultraspectral data into secure, evidence-backed intelligence products. The Product Intelligence Engineer will develop agentic workflows, integrate retrieval and tools, create reports, and design human-in-the-loop experiences to aid customers in making operational decisions.
Requirements
- 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.
Nice To Haves
- 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.
Responsibilities
- 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.
Benefits
- 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
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
