AI Automation Engineer

Title: Intelligent Automation Systems Engineer
Location: Manhattan, NY (Hybrid with On-Site Preferred)

About the Role:
Join a cutting-edge engineering team leading the convergence of AI and robotics to transform how automation operates across sectors like manufacturing, logistics, and high-tech R&D. This is a high-impact opportunity for someone passionate about pushing the boundaries of what’s possible in intelligent machine behavior and industrial autonomy. The ideal candidate will design, deploy, and refine AI-integrated automation workflows that improve system learning, adaptability, and performance—all while working with top-tier engineers in a state-of-the-art lab and field environment.

Key Responsibilities:

• Architect adaptive automation systems that integrate rule-based programming, robotics, and machine learning technologies.
• Develop interfaces that allow real-time communication between AI algorithms (e.g., vision, language, or reinforcement learning) and automation hardware such as PLCs and robotic arms.
• Enable autonomous decision-making capabilities in industrial scenarios through intelligent failure recovery and process optimization.
• Collaborate closely with controls, software, and mechanical engineering teams to embed AI into core automation pipelines.
• Build monitoring tools to oversee real-time AI behavior, system health, and performance KPIs.
• Drive ongoing improvement through audits, metrics analysis, and machine learning model feedback.

Highlighted Projects:

• Self-calibrating robotic systems using machine vision and adaptive learning.
• AI-based schedulers that dynamically allocate tasks across distributed robotic platforms.
• Real-time anomaly detection models with automated system correction for operational resilience.

Qualifications:

Required:

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, Mechatronics, or a related field.
• 3+ years of experience in automation or robotics engineering, with demonstrable work on AI/ML integration.
• Strong proficiency in Python and experience with industrial communication protocols such as MQTT, OPC UA, or Modbus.
• Experience deploying machine learning models in live systems (scikit-learn, PyTorch, or TensorFlow).
• Solid understanding of embedded control systems, sensors, and industrial robotics.

Preferred:

• Experience with real-time systems and robotics middleware such as ROS or ROS2.
• Knowledge of Docker or edge-computing platforms.
• Familiarity with predictive analytics, reinforcement learning, or intelligent maintenance frameworks.

Why Apply:

• Be part of pioneering projects that integrate AI into physical automation for real-world transformation.
• Work hands-on in a collaborative environment with access to advanced robotics labs and deployment sites.
• Receive a competitive compensation package including salary, equity, and comprehensive benefits.
• Thrive in a forward-thinking culture with strong mentorship and innovation at its core.