Fundamental

Fundamental is hiring an MLOps Engineer to build scalable machine learning infrastructure, model-serving systems, and high-performance inference architectures for enterprise AI. The role combines ML platform engineering, cloud infrastructure, observability, and data pipelines.

Backend Engineer responsible for building reliable, scalable Extensions capabilities that power enterprise AI decision-making. The role combines Python backend development, distributed workflows, performance optimization, and close collaboration with data science teams.

Fundamental is hiring a hands-on Solutions Architect to help enterprise customers deploy predictive applications using its NEXUS tabular foundation model. The role combines customer strategy, solution architecture, data science, machine learning, and production implementation, with 50% travel.

Build and optimize large-scale neural network models for enterprise tabular decision-making, with a strong focus on Python/Rust systems performance. You’ll collaborate with ML researchers to productionize new capabilities and shape the architecture of Fundamental’s ML systems.

Senior Applied Research Engineer focused on making large-scale foundation model training and serving faster, more efficient, and more reliable. You’ll optimize distributed multi-GPU workloads, develop low-level kernels when needed, and partner closely with ML researchers to productionize new ideas.

Build the integration layers, interfaces, and production applications that help enterprise customers successfully adopt Fundamental’s NEXUS AI platform. This customer-facing role combines full-stack development, enterprise integrations, and technical relationship management from proof of value through post-implementation.