Autonomous Robotics ML Engineer

Built Robotics Inc; United States; Remote; USD 140,000 - 185,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

401(k) matching

Paid time off

TSA PreCheck

Catered lunch

Steel-toe boots

Gym membership

Job summary

Built Robotics Inc is seeking a machine learning engineer to design edge ML systems for autonomous construction robots and to build scalable training pipelines and computer vision models.

You will analyze large datasets, improve object recognition and scene understanding, and integrate cloud-based AI tools into the autonomy stack. Competitive compensation and equity accompany a comprehensive benefits package.

Qualifications

• BS, MS, or PhD in computer science, artificial intelligence, machine learning, robotics, or related field.
• 3+ years of experience building and deploying machine learning systems.
• Expertise in Python and ML frameworks such as PyTorch or TensorFlow.
• Experience building distributed ML training systems and data pipelines.
• Robotics or autonomous systems experience is a plus.

Responsibilities

• Design and develop edge machine learning systems that to improve the autonomy and safety of our construction robots
• Build scalable ML infrastructure for model training, validation, deployment, and monitoring
• Develop and optimize computer vision and sensor fusion models for construction environments
• Analyze large-scale operational datasets to improve model performance and reliability
• Improve object recognition, scene understanding, and autonomous decision-making systems
• Integrate cloud-based commercial and open-source AI tools into our autonomy stack

Skills

Python

Machine Learning

Robotics/Autonomy

Education

BS/MS/PhD in CS/AI/ML/Robotics

Tools

PyTorch

TensorFlow

Job description

Built Robotics Inc is seeking a machine learning engineer to design edge ML systems for autonomous construction robots and to build scalable training pipelines and computer vision models.

You will analyze large datasets, improve object recognition and scene understanding, and integrate cloud-based AI tools into the autonomy stack. Competitive compensation and equity accompany a comprehensive benefits package.