Who are We? 
 
 
 
 
 Field AI   is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications. 
 
 Learn more at https://fieldai.com. 
 
 
 
 
 About the Job 
 
 
 
 
 As an ML Engineer at Field AI, you will help build the next-generation Field Foundation Model (FFM) , powering a global fleet of autonomous robots deployed across diverse environments. Your contributions will directly shape how we scale – through advances in model architecture, training methodologies, and deployment strategies. You’ll collaborate closely with machine learning scientists, software engineers, and robotics experts to design and implement FFM capabilities that generalize across tasks and environments. Beyond model development, you’ll also support deployment and monitoring to ensure smooth integration and reliable real-world performance. This role offers the opportunity to work with cutting-edge technologies, solve complex challenges, and directly impact large-scale robot deployments.
What You’ll Get To Do:
• Design, train, and deploy state-of-the-art machine learning models for end-to-end learning based navigation stack.
• Work with deep learning architectures such as transformers, convolutional networks to capture complex decision making.
• Leverage imitation learning and reinforcement learning to advance planning and reasoning of our models.
• Explore novel data generation and collection pipelines to enrich training datasets.
• Assist with deploying machine learning models into production environments
• Continuously monitor models in production, detecting model drift, and automating retraining processes as applicable
• Troubleshoot issues related to model deployment, performance, and system integration.
The Extras That Set You Apart:
• Publications in top tier ML or robotics conferences