About the job
About Aizen
At Aizen, our goal is to simplify AI while maximizing its potential. We offer a comprehensive platform that efficiently manages the entire AI pipeline—from data ingestion and orchestration to model training, deployment, and monitoring. This allows businesses to concentrate on what truly matters: creating and scaling innovative AI solutions without unnecessary complications.
Frustrated by cumbersome AI workflows and makeshift solutions that impede AI adoption, we started Aizen. Now, we support companies of all sizes, from budding startups to Fortune 500 giants, in enhancing their AI capabilities and scaling seamlessly. By transforming the way AI is developed, deployed, and overseen, we are making AI more accessible and impactful than ever. If you are passionate about developing cutting-edge technology, addressing real-world challenges, and collaborating with a top-notch engineering team, we would love to connect with you.
About the Team
Aizen was established by a group of serial entrepreneurs who possess extensive expertise in data storage, distributed systems, and real-time AI architecture. With a track record of building and scaling tech companies—some achieving successful exits of over $1 billion—our team understands the key elements required to create an exceptional product and company. We have crafted Aizen from the ground up to streamline the AI pipeline, enhance performance, and ensure AI is genuinely accessible to enterprises of all sizes.
About the Role
As a Machine Learning Engineer at Aizen, you will play a pivotal role in constructing and refining the AI pipelines that drive our comprehensive AI platform. You will engage with various aspects of the stack, from data ingestion and model training to real-time inference and monitoring, guaranteeing smooth AI deployment at scale. Whether you are an entry-level engineer eager to advance or a senior engineer prepared to spearhead significant projects, this role presents the chance to tackle challenging ML problems, boost automation, and contribute to the future of AI infrastructure.
Core Responsibilities
AI Pipeline Development – Design, construct, and optimize comprehensive AI pipelines for data ingestion, training, deployment, and real-time inference, ensuring smooth integration with MLOps and infrastructure systems.
Model Training & Deployment – Create training and fine-tuning workflows for ML models, focusing on efficiency, scalability, and reproducibility across cloud, on-premise, and edge environments.
Backend & API Development – Develop and integrate scalable backend services and APIs for model inference...

