Machine Learning Engineer

AMP applies AI-powered sortation technology to modernize recycling infrastructure and improve resource recovery. The Machine Learning Engineer will develop, evaluate, and productionize deep learning and computer vision models, collaborate across AI and infrastructure teams, and support AMP’s machine learning infrastructure.

Responsibilities:

• Experiment with modern neural network architectures or techniques driven by research publications
• Design and implement machine learning perception solutions in new domains
• Design and execute experiments to validate R&D deep learning approaches
• When experiments have positive results, design a path to production to deliver impact to our facilities
• Collaborate with AI Data Team project managers, ML modeling engineers, and Cloud infrastructure engineers
• Serve as a subject matter expert for experiment design and statistical modeling for the Software organization, applying these skills to non deep learning projects when relevant
• Help us support and improve our ML infrastructure

Requirements:

• Master's degree in Computer Science/Machine Learning or similar, or equivalent combination of technical education and work experience
• 4+ years' experience writing production-level code in python
• 4+ years of experience implementing statistical models in production environments
• Proficiency with professional software engineering practices; including coding standards, code reviews, source control management, build processes, testing, and operations
• Strong familiarity with PyTorch
• Strong familiarity with experiment design and experiment execution
• Research fluency with a deep learning domain
• Prolonged periods of sitting at a desk and working on a computer
• Must be able to lift up to 15 pounds at a time
• Full-remote with regular travel to AMP's Louisville CO HQ or
• Hybrid or full time in-office at AMP's Louisville CO HQ
• 3+ years of experience with deep learning, particularly computer vision
• Proficiency with neural network quantization, acceleration, and inference tools, particularly TensorRT
• Familiarity and interest in research-level mathematics
• Proficiency working with SQL databases and data pipelines
• Experience deploying large-scale and small-scale models in low-latency environments
• Startup ready mentality
• Passion for recycling, robotics and changing the world