Onsite ML Engineer for Factory Automation

AIC; New York (NY); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

Medical, Dental, Vision benefits

Unlimited PTO

Equity

Job summary

AIC is a software-led industrial holding company deploying its Decision Physics framework to modernize factory decision-making on-site in Brooklyn Navy Yard or El Segundo. The role blends software and hardware, requiring 2+ years of ML and software experience, strong statistics, data pipelines, and a proven ability to ship end-to-end systems on the factory floor.

Join a hard-tech, manufacturing-facing environment with extensive on-site work, and help unlock trapped capacity by delivering

Qualifications

• 2+ years of experience in machine learning and software engineering in a fast and collaborative production environment
• Statistics knowledge including classical methods, Bayesian methods, uncertainty quantification
• Experience taking models from notebook to production: feature pipelines, evaluation, monitoring, retraining
• Experience with computer vision, time-series and sensor data, causal inference or econometrics, optimization or OR
• Strong communication and stakeholder management skills
• Knowledge designing data-intensive applications and APIs or backend systems
• Hard-tech, robotics, and manufacturing background is a big plus

Responsibilities

• Embed on-site with design partners and manufacturers.
• Build trust across the full vertical from GM to the technician running the station.
• Develop genuine understanding of partner shops including history, constraints, people, and physics.
• Build models on factory data and ship ML that touches hardware (vision, part IDs, document parsing).
• Quantify how floor changes affect EBITDA and margins.
• Translate observations into concrete requirements and lead code on-site and at HQ.
• Write production code across the full stack: data model, ETL, backend, frontend, APIs, and ML pipelines.
• Run the process-engineering side of deployment with training and change management.
• Own outcomes, not just deliverables; success measured by operational maturity and financial impact.

Skills

Machine learning

Software engineering

Statistics

Computer vision

Time-series

Sensor data

Data modeling

ETL

Hardware integration

DevOps

APIs

Infra

Frontend

Operations research

Manufacturing background

Education

Graduate education (CS/Math/Applied fields)

Tools

Git

ML frameworks

Job description

AIC is a software-led industrial holding company deploying its Decision Physics framework to modernize factory decision-making on-site in Brooklyn Navy Yard or El Segundo. The role blends software and hardware, requiring 2+ years of ML and software experience, strong statistics, data pipelines, and a proven ability to ship end-to-end systems on the factory floor.

Join a hard-tech, manufacturing-facing environment with extensive on-site work, and help unlock trapped capacity by delivering