ML Engineer – Computer Vision for Production Recycling (Remote)

AMP; Louisville (KY); Hybrid; USD 162,000 - 170,000; Full time

Benefits offered by this job

Medical Insurance

Dental & Vision

401(k)

Paid Time Off

Flexible Hours

Growth Opportunities

Job summary

AMP Robotics is hiring a Machine Learning Engineer focusing on developing deep learning and computer vision models and shipping them to production. You will contribute to state-of-the-art computer vision research, working as an individual contributor on the perception team to move models from ideation to production.

Ideal candidates hold a Master’s in CS/ML or equivalent, with 3+ years Python and production-level experience, and strong PyTorch expertise.

Qualifications

• Master's degree in CS/ML or equivalent.
• 3+ years writing production-level Python code.
• 3+ years implementing statistical models in production.
• Familiarity with PyTorch and experiment design.
• Research fluency in deep learning domain.

Responsibilities

• Experiment with modern neural network architectures and publications-based techniques.
• Design and implement ML perception solutions in new domains.
• Design and execute experiments to validate R&D approaches.
• Translate successful experiments into production to impact facilities.
• Collaborate with AI Data Team and Cloud infra engineers.
• Provide SME guidance on experiment design and statistical modeling.

Skills

Python production code

Statistical models in production

PyTorch

Experiment design

Deep learning research

Education

Master's degree in Computer Science/Machine Learning or equivalent

Tools

Python

Job description

AMP Robotics is hiring a Machine Learning Engineer focusing on developing deep learning and computer vision models and shipping them to production. You will contribute to state-of-the-art computer vision research, working as an individual contributor on the perception team to move models from ideation to production.

Ideal candidates hold a Master’s in CS/ML or equivalent, with 3+ years Python and production-level experience, and strong PyTorch expertise.