Software Engineer, Perception

at  Agtonomy

ABOUT US

Agtonomy is pioneering advanced automation and AI solutions to transform agriculture and beyond. Initially focused on specialty crops, our TeleFarmer™ platform addresses labor-intensive needs with automation, turning conventional equipment into autonomous machines. By partnering with leading manufacturers like Doosan Bobcat, we integrate smart technology into tractors and other machinery, enhancing safety and efficiency. As we expand into ground maintenance and other industrial applications, our expert team continues to address key challenges with labor shortages, sustainability and profitability across various industries.

ABOUT THE ROLE

As a Perception / Machine Learning Engineer on the Autonomy Team, you will play a key role in solving challenging perception problems in outdoor vehicle automation. Leveraging your experience, you will implement state-of-the-art ML perception techniques to improve how Agtonomy’s tractors perceive and understand the environments where they operate. You will work closely with embedded, localization, and planning engineers on the team to design and evolve the upstream and downstream interfaces of the perception system. This role is perfect for someone who loves implementing ML to tackle real world problems, and is excited about applying their experience to make robots perceive in rugged, agricultural environments.

WHAT YOU’LL DO

• Applying machine learning to solve challenging perception problems for autonomous systems (e.g. object detection, semantic segmentation, instance segmentation, dense depth, optical flow, tracking, etc.).
• Driving the architecture, deployment, and performance characterization of our deep learning models.
• Refining and optimizing models for low-latency inference on embedded hardware.
• Designing and building cloud-based training and labeling pipelines.
• Collaborating with the hardware and embedded teams on sensor selection and vehicle packaging given safety requirements.
• Writing performant, well-tested software, and improving code quality of the entire Autonomy team through code and design reviews.