AI infrastructure for training and inference across clouds
FlexAI builds a software-defined cloud platform that orchestrates AI workloads like inference, fine-tuning, and training across multiple clouds, accelerators, and data centers. It serves AI teams, startups, and enterprises by abstracting hardware complexity, enabling faster deployment, better efficiency, and avoiding vendor lock-in. This matters as it addresses AI compute shortages and optimizes heterogeneous compute usage.
New grad software engineer building reliable AI infrastructure products, APIs, and scalable features. Requires BS/MS in CS, strong coding in Python/Go/Java/JS, algorithms knowledge, and internship experience.
Designs, develops, and optimizes core runtime infrastructure for distributed AI training and inference using PyTorch-based stack. Requires 8+ years in systems engineering, deep learning runtimes, Python/C++, and multi-node GPU workloads.
Architects and builds high-performance Golang backend services for AI PaaS platform, focusing on distributed systems, GPU orchestration, model deployment, and cloud-native infrastructure. Requires 5+ years experience with expert Golang and Kubernetes proficiency.
Build end-to-end features for AI compute platform including React UIs, Python/Node.js APIs, data workflows, and compute integrations. Requires 5+ years full stack experience, React, Python/FastAPI or Node.js, and startup environment comfort.