Learning Process Engineer U.S

We’re building the next generation of AI‑powered productivity tools for autonomous building management, with seamless interaction between humans and machines at the core. Our team combines deep expertise in AI with elegant product design to create experiences that are natural, intuitive, and delightful. If you’re excited about attracting new users and championing our products while helping us accelerate and strengthen our frameworks, this role is for you.

Passive Logic is the first fully autonomous platform for buildings. We’ve reinvented the fundamental principles of automation to democratize technology, optimize buildings, and reduce the world’s carbon footprint. We are a team of technologists, engineers, and creatives dedicated to making a sustainable impact through real‑world solutions.

We are looking for team members who have a passion for technology and want to work on cutting‑edge problems with real‑world solutions. Our culture is built on bringing together the most talented engineers, thinkers, and creatives—backed by the world’s leading investors—working together to make the future a reality.

This is a career‑defining opportunity to play a crucial role in a hyper‑scale AI company that is transforming the future of autonomous systems, energy, and the built environment. We are looking for a Learning Process Engineer to design and implement the technical frameworks through which our Qortex engine learns, adapts, and improves. This role blends machine learning, data engineering, and graph‑based knowledge modeling.

You will architect the pipelines, feedback loops, and graph‑driven logic that enable the system to continuously refine its performance.

If you thrive on building scalable learning architectures that combine AI with graph‑based data systems, this is the role for you.

• Architect feedback pipelines: Build and maintain data ingestion and labeling processes that transform user interactions into structured learning signals.
• Design graph‑based knowledge structures: Model, update, and optimize workflows in a graph database (e.g., Neo4j, Arango
  
  DB, Weaviate, or similar).
• Implement adaptive logic: Use graph queries and embeddings to inform recommendations, predictions, and workflow adaptation.
• Integrate human‑in‑the‑loop learning: Deploy mechanisms that incorporate user corrections and contextual feedback into graph representations and model updates.
• Collaborate with ML and software engineers: Define retraining strategies, model evaluation criteria, and experiment frameworks that leverage graph‑based data.
• Automate performance monitoring: Develop dashboards and metrics for tracking how graph‐driven learning impacts system accuracy, adoption, and efficiency.

If your experience does not meet all our posted requirements below, we’d still love to hear from you. We are looking for practitioners who are passionate about understanding people, committed to lifelong learning, and driven by the love of what they do. If that’s you, please apply!

• Technical background in computer science, AI/ML, data engineering, or knowledge systems.
• Experienced with graph databases (Neo4j, Tiger Graph, Weaviate, Neptune), Python/C++, graph query languages (Cypher, Gremlin, Graph
  
  QL, SPARQL), graph ML/embeddings, and building ETL pipelines, event‑driven systems, and real‑time feedback loops.
• Understanding of feedback‑driven model improvement, reinforcement learning, or adaptive systems.
• Experience working cross‑functionally with engineers, designers, and product managers.
• Analytical mindset: ability to define success metrics, run experiments, and interpret results.
• Excellent communication skills and a collaborative, problem‑solving approach.
• Background in process engineering, systems design, product operations, or applied AI/ML.
• Strong systems thinking: ability to model complex workflows and simplify them into actionable processes.
• Familiarity with human‑in‑the‑loop learning, adaptive systems, or feedback‑driven workflows.

Proven experience: 5+ years in developing software with an ecosystem nature.

Exceptional communication skills: Ability to craft narratives…