Remote Graph Knowledge Temporal Jobs

Many of the paradigms for how data and knowledge bases are organized assume human consumers and constraints. This is no longer true in a world of LLMs!

and other knowledge stores, ensuring our agents continuously adapt to feedback and learn.

Temporal Technologies is an Equal Opportunity Employer.

AI researchers and engineers—we’re building continuous‑learning agents driven by our Learning Engine, a modular framework that lets agents learn from human knowledge

Uses extensive experience and knowledge to resolve complex problems.

What you’ll do: Develop spatio-temporal machine learning models for detection, multi-sensor fusion, segmentation, etc.

Working knowledge of privacy and compliance practices (GDPR/CCPA) in data workflows.

Working knowledge of privacy and compliance practices (GDPR/CCPA) in data workflows.

Working knowledge of privacy and compliance practices (GDPR/CCPA) in data workflows.

Dynamical systems simulation knowledge Knowledge of Analog and Mixed-Signal circuit design: understand transistor

Experience with Generative AI application patterns such as RAG, knowledge-graph, etc.

Experience with LLM applications, including retrieval, evaluation, guardrails, and knowledge graphs.

Temporal-data expertise: revisions, event time versus knowledge time, reproducibility, and point-in-time querying.

Bonus Experience with consortium, data cooperative, or information-sharing products Background in entity resolution or graph-based

Experience with PyTorch internals: autograd, custom modules, low-level ops; familiarity with torch.compile or similar graph capture/compile flows.