Industrial Autonomy Engineer — Real-Time Control

Lumaril Corporation; New York (NY); On-site; USD 175,000 - 300,000; Full time

Benefits offered by this job

Daily lunch at the office

Fully paid medical, dental, and vision

401k through Betterment

Job summary

Lumaril Corporation is seeking an engineer to build and deploy real-time control systems at customer facilities. You will work with customers and hardware partners to design complete, end-to-end systems that integrate sensors, PLC data, and control policies.

We apply robotics techniques to make industrial processes observable and controllable, starting with reliable improvements and expanding across domains.

Qualifications

• 2–5 years applying robotics techniques in industry, research, or both.
• Background spanning robotics, autonomous vehicles, defense/aerospace, industrial automation, or physical AI.
• Familiarity with robotics tooling and simulation environments.

Responsibilities

• Collaborate with customers to understand real-world constraints and decompose problems into subsystems.
• Design and deploy real-time control systems in production environments.
• Develop perception over visual/PLC data, state estimation, and model-based or learned control policies.
• Maintain infrastructure and libraries enabling closed-loop decision-making in industrial settings.
• Deploy systems that adjust control logic, impacting output, yield, and efficiency.
• Balance rapid customer delivery with long-term product development to create reusable components.

Skills

Robotics perception

State estimation

Controls

Simulation

Full-stack debugging

Clear communication

Travel 15-35%

Education

MS/PhD in robotics or related field

Tools

PLC/SCADA

Job description

Lumaril Corporation is seeking an engineer to build and deploy real-time control systems at customer facilities. You will work with customers and hardware partners to design complete, end-to-end systems that integrate sensors, PLC data, and control policies.

We apply robotics techniques to make industrial processes observable and controllable, starting with reliable improvements and expanding across domains.