A.I. Data Quality Control Technician

AMP Robotics is a pioneer and industry leader in artificial intelligence (AI), robotics, and infrastructure for the waste and recycling industry. We apply AI-powered automation to economically and sustainably improve our global recycling system.

Headquartered in Louisville, Colorado, the Denver Post and BuiltIn Colorado have recognized AMP as one of the state's top workplaces. AMP also has operations and career opportunities outside of Atlanta and Cleveland, as well as in Europe. We’re fostering an environment where passionate individuals can grow and create impact. We seek unconventional thinkers to join our mission to enable a world without waste; at AMP, your contributions have meaning and can spur change. With backing from top-tier investors and national recognition including North American Cleantech Company of the Year and Forbes’ most promising AI companies, we’re always seeking ways to better our operations, raising the bar on innovation, and looking to collaborate and improve in what we do. Learn more at AMPRobotics.com.

AMP Robotics is hiring a Part Time (20 hours / week max) A.I. Data Quality Control Technician. This person can be Remote in the U.S.

This person will be reporting to the Engineering Manager of Team Data within the Brain Team. AMP’s Team Brain is responsible for generating and improving our waste imagery datasets, and developing ML models. Together, our models and datasets drive our fleet of robots by empowering them to correctly identify the material they are sorting. AMP’s AI Data QC Technicians will help improve our AI performance in mission critical applications and new verticals by reviewing and correcting the annotated waste characterization data that is the backbone of our AI.

As our A.I. Data Quality Control Technician, you will work to:

• Become an expert in industrial sortation, particularly in material classification of single stream recycling, construction and demolition, and organics.
• Review annotated images of waste classification and make corrections to data where necessary.
• Communicate common quality problems with rest of Data team and external annotation partners.
• Recommend potential areas of improvement for data clean up based on common errors seen

Supervisory Responsibilities:

• None

The successful candidate will have:

Required:

• High school diploma or equivalent
• Strong attention to detail

Preferred:

• Passion for recycling/green tech
• Experience working with offshore teams

Education:

• High school diploma or equivalent

Experience:

• This is an entry level position! No prior experience in the field is required

Working Conditions/Physical Demands:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job.  Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Prolonged periods of sitting at a desk and working on a computer.
• Must be able to lift up to 15 pounds at times.

Working Location(s):

• Remote, with hybrid option available at our Louisville, CO location

Travel Requirements:

• None

AMP provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

Other duties:

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

Compensation: $15-$25/hr, depending on experience. This position will be a max of 20 hours a week. 

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