Founding Technical Staff, Machine Learning Engineer

AIC•New York City, NY

1d•Onsite

About The Position

AIC is a software-led industrial holding company that has developed AIC OS, an operating system based on Decision Physics™. This system is deployed alongside the people operating production lines to improve their efficiency. The company's team embeds on-site with partners, deploying software that enhances operator capabilities within weeks and transforms factory operations. AIC focuses on solving complex industrial challenges rather than offering standard SaaS licenses, and they refer to themselves as Software Industrialists.

Requirements

1-10 years of experience in Machine Learning Engineering development.
Fundamental knowledge of ETL, backend services, micro-frontends, algorithms, hardware integrations, ML pipelines, and infrastructure.
1+ years of experience shipping production-grade code.
Strong Emotional Quotient (EQ) and communication skills.

Nice To Haves

Background or adjacency in hard-tech, robotics, and manufacturing.

Responsibilities

Embed on-site with design partners for significant periods, treating their factory floor as a primary workspace.
Build trust across all levels of the partner's organization, from management to floor technicians.
Develop a deep understanding of each partner's operational processes, including their history, constraints, personnel, and the physics involved.
Translate observations into concrete software requirements.
Build, ship, and maintain software, both independently and by coordinating engineers on-site and at headquarters.
Write production code across the full technology stack, including ETL, backend services, micro-frontends, algorithms, hardware integrations, ML pipelines, analyses, and infrastructure.
Manage the process-engineering aspects of software deployment, ensuring software and operational changes are synchronized.
Conduct cultural work, including training, change management, developing work instructions, and engaging in one-on-one discussions with skeptics.
Take ownership of outcomes, focusing on the partner's operational maturity and financial results rather than just shipped features.