Machine Learning Engineer, Autonomy

• Design and optimize computer vision and machine learning models for perception tasks like segmentation and depth estimation.
• Manage the full machine learning development lifecycle from prototyping to production deployment on edge and cloud platforms.
• Collaborate with cross-functional engineering teams to integrate perception models into autonomous machinery.
• Evaluate and enhance model performance through testing and metric analysis on large datasets.
• Apply advanced machine learning and computer vision methods to address practical challenges in autonomous agriculture.

• Bachelor’s or Master’s Degree in Computer Science or a related field; graduate degree preferred.
• At least 2 years of experience developing high-performance ML systems, particularly training and optimizing deep neural networks for segmentation, depth, and perception tasks.
• Proficiency in Python and PyTorch or TensorFlow.
• Strong understanding of vision and deep learning fundamentals.
• Effective communication skills for interdisciplinary collaboration and model integration.

Preferred:

• Experience building and deploying end-to-end ML pipelines.
• Knowledge of edge deployment and real-time optimization.
• Background in computer vision, machine learning, and robotics projects.
• Familiarity with multi-view geometry, SLAM, vehicle autonomy, and robotics libraries such as ROS or ROS2.
• Experience in metrics implementation and dashboarding.

• The pay range for this role is between $113,000 and $202,000 per year, depending on experience, qualifications, education, location, and skills.
• Eligible for an annual performance bonus and a competitive benefits package.

The organization operates in the agricultural and construction technology sector, addressing challenges related to labor scarcity and the need for safer, more sustainable machinery. It focuses on developing intelligent autonomous and precision equipment through advancements in artificial intelligence, machine learning, computer vision, and robotics. Acting as a research and development hub, the program creates innovative platforms and products that deliver value in industries such as agriculture and construction, contributing to technical breakthroughs and environmental impact.

1. About the Opportunity:

The Machine Learning Engineer, Autonomy role is focused on building and enhancing the perception stack for an autonomous tractor program. The position involves developing computer vision and machine learning models and associated training and testing pipelines that improve safety and performance in real-world production environments. This role bridges prototyping and production-scale deployment, playing a critical part in advancing autonomous agricultural technologies.