Own reusable utility ML libraries for forecasting, disaggregation, demand response, detection, and asset health. - Own the simulation engine with Rust and Python bindings, including validation methodology. - Own the grid-data toolkits including protocol codecs and synthetic scenario generators.
Own the full ML delivery lifecycle from data discovery to deployment, monitoring, and retraining.
Build forecasting and detection models robust to real-world data quality issues and defend tradeoffs.
Maintain client-facing presence and feedback loop, shipping usable capability like FastAPI, React, or scheduled jobs.
We accelerate positive impact in critical industries through AI transformation, specializing in physics-informed ML and enterprise AI solutions for climate and sustainability. We're a fast-growing, profitable public benefit corporation founded in 2024, working with category leaders in real estate, energy, logistics, and utilities.
Design, build, and maintain core AI capabilities that power intelligent experiences across the platform.
Develop reusable capabilities for model integration, reasoning, and evaluation.
Optimize AI systems through experimentation, quantitative evaluation, and iterative refinement.
Legion embeds intelligence inside complex systems, unlocking data and accelerating human workflows for government and enterprise. They collaborate with world-class partners like Palantir and Nvidia, building intelligent infrastructure with a team of bold thinkers.
Support training, fine-tuning, and evaluation of neural foundation models.
Build and maintain data pipelines for petascale neurobehavioural datasets.
Prototype tools and demos to apply trained models to robotics and embodied AI tasks.
Netholabs builds AI grounded in biological intelligence by recording petascale neurobehavioural data to train neural foundation models. They are a small, fast-moving research team focused on AI, robotics, and personalized intelligence.