Remote Machine Learning Engineer — Perception & CV

AMP; United States; Remote; USD 162,000 - 170,000; Full time

Job summary

AMP Robotics is seeking a Machine Learning Engineer to join our perception team and advance deep learning methods for production-grade computer vision. You will work on state-of-the-art models, implement experiments, and partner with data, ML, and cloud teams to scale results to facilities worldwide.

The role emphasizes hands-on development, model deployment, and maintaining cutting-edge ML infrastructure with a startup-spirited culture in a globally deployed environment.

Qualifications

• Master's degree in Computer Science or Machine Learning or equivalent.
• 3+ years' experience writing production-level Python code.
• 3+ years' experience implementing statistical models in production.
• Strong familiarity with PyTorch and experiment design.
• Experience deploying ML models in production and with CV areas.

Responsibilities

• Experiment with modern neural networks and publishable techniques.
• Design and implement ML perception solutions for new domains.
• Run experiments to validate deep learning approaches and bring them to production.
• Collaborate with AI Data Team, ML engineers, and Cloud infra engineers.
• Provide SME input on experiment design and statistical modeling for software projects.

Skills

Python

Production code

Statistical models

PyTorch

Experiment design

Deep learning

Computer vision

TensorRT

SQL

Data pipelines

Education

Master's degree in Computer Science or Machine Learning

Tools

PyTorch

TensorRT

Job description

AMP Robotics is seeking a Machine Learning Engineer to join our perception team and advance deep learning methods for production-grade computer vision. You will work on state-of-the-art models, implement experiments, and partner with data, ML, and cloud teams to scale results to facilities worldwide.

The role emphasizes hands-on development, model deployment, and maintaining cutting-edge ML infrastructure with a startup-spirited culture in a globally deployed environment.