Small-scale ocean processes are known to modulate nutrient availability in the upper ocean, yet nutrient variability at scales of O(1) day and O(1) km has remained challenging to characterize from observations. Here, we show that small-scale nutrient information can be inferred from the 2019 Southern Ocean Glider Observations of Submesoscales (SOGOS) field experiment using random forest regression (RFR). In this experiment, a Biogeochemical-Argo float with coarse-resolution nutrient sensing capabilities was co-deployed with two rapid-sampling Seagliders to autonomously observe a turbulent region by the Southwest Indian Ridge over ∼80 days in austral winter. Since the Seagliders did not measure nitrate directly, we used RFR to estimate nitrate from temperature, salinity, pressure, and oxygen data. We trained the RFR to represent regional relationships between these variables and nitrate using nearby ship-based and BiogeochemicalArgo float observations. When tested on nitrate data from the SOGOS float, our RFR reproduced these measurements to within 3% accuracy and outperformed existing, widely-used global nutrient estimation routines trained primarily on ship-based data. Applying the RFR to the Seaglider observations generated novel high-resolution nitrate distributions, which extend to 1000 m with horizontal resolution of ∼1.5 km and 2–3 hours compared to ∼75 km and 5 days for the SOGOS float. The nitrate estimates along the Seaglider tracks, coupled with Seaglider observations of other properties, provide evidence that vigorous stirring downstream of the ridge enhances small-scale biogeochemical variability and increases nutrient availability in the upper ocean. These results highlight the importance of oceanic turbulence in influencing biological productivity.