<div><b style="font-size:18px;">About Us</b></div><div><br></div><div><span style="font-size:15px;">Agtonomy brings intelligent automation to agriculture, turf, and other demanding industries through Physical AI and software services. By partnering with trusted equipment manufacturers, we deliver factory-fit technology that transforms industrial machines into smart, efficient solutions built for safety and performance. Our team combines expertise in technology, product development, and industry knowledge to address critical challenges like labor shortages, sustainability, and productivity. We’re looking for people who want to work in a collaborative, fast-moving environment where their ideas can make a real impact.</span></div><div><br></div><div><b style="font-size:18px;">About the Role</b></div><div><br></div><div><span style="font-size:11pt;">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.</span></div><br><br><h3>What You'll Do</h3><ul><li>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.).</li><li>Driving the architecture, deployment, and performance characterization of our deep learning models.</li><li>Refining and optimizing models for low-latency inference on embedded hardware.</li><li>Designing and building cloud-based training and labeling pipelines.</li><li>Collaborating with the hardware and embedded teams on sensor selection and vehicle packaging given safety requirements.</li><li>Writing performant, well-tested software, and improving code quality of the entire Autonomy team through code and design reviews.</li></ul><h3>What You'll Bring</h3><ul><li>5+ years of experience in software development for problems involving computer vision, machine learning, and robotic perception techniques.</li><li>Foundational understanding of deep learning: model layer design, loss function intuition, training best practices.</li><li>Experience handling large datasets efficiently and organizing them for training and evaluation.</li><li>Experience curating synthetic and real-world image datasets for training.</li><li>Strong proficiency in modern C++ and Python and experience writing efficient algorithms for resource-constrained embedded systems.</li><li>Ability to thrive in a fast-moving, collaborative, small team environment with lots of ownership.</li><li>Excellent analytical, communication, and documentation skills with demonstrated ability to collaborate with interdisciplinary stakeholders outside of Autonomy.</li><li>An eagerness to get your hands dirty by testing your code on real robots at real customer farms (gives “field testing” a whole new meaning!).</li></ul><h3>What Makes You a Strong Fit</h3><ul><li>Experience architecting multi-sensor ML systems from scratch.</li><li>Experience with compute-constrained pipelines: optimizing models to balance the accuracy vs. performance tradeoff, leveraging TensorRT, model quantization, etc.</li><li>Experience implementing custom operations in CUDA.</li><li>MS or PhD in Robotics, Computer Science, Computer Engineering, or a related field.</li><li>Publications at top-tier perception/robotics conferences (e.g. CVPR, ICRA, etc.).</li><li>Passion for sustainable agriculture and electric vehicles.</li></ul><br><div>Benefits:</div><div><br></div><div>• 100% covered medical, dental, and vision for the employee (cost plus partner, children, or</div><div>family is additional)</div><div>• Commuter Benefits</div><div>• Flexible Spending Account (FSA)</div><div>• Life Insurance</div><div>• Short- and Long-Term Disability</div><div>• 401k Plan</div><div>• Stock Options</div><div>• Collaborative work environment working alongside passionate mission-driven folks!</div><div><br></div><div>Our interview process is generally conducted in five (5) phases:</div><div><br></div><div>1. Phone Screen with People Operations (30 minutes)</div><div>2. Video Interview with the Hiring Manager (45 minutes)</div><div>3. Coding Challenge and Technical Challenge  (1 hour with an Autonomy Engineer)</div><div>4. Panel Interview (Video interviews scheduled with key stakeholders, each interview will be 30 to 45 minutes)</div><div>5. Final Interviews (CEO and CFO 30 minutes each)</div>

<p>Agtonomy is a hybrid autonomy and tele-assist platform for agriculture vehicles. We partner with established equipment manufacturers to transform tractors and agriculture machines into autonomous and remote-controlled equipment that is accessible to local farmers.</p>

Software Engineer, Perception

<div><b>About Us</b></div><div><br></div><div><span>Agtonomy brings intelligent automation to agriculture, turf, and other demanding industries through Physical AI and software services. By partnering with trusted equipment manufacturers, we deliver factory-fit technology that transforms industrial machines into smart, efficient solutions built for safety and performance. Our team combines expertise in technology, product development, and industry knowledge to address critical challenges like labor shortages, sustainability, and productivity. We’re looking for people who want to work in a collaborative, fast-moving environment where their ideas can make a real impact.</span></div><div><br></div><div><b>About the Role</b></div><div><br></div><div><span>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.</span></div><br><br><h3>What You'll Do</h3><ul><li>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.).</li><li>Driving the architecture, deployment, and performance characterization of our deep learning models.</li><li>Refining and optimizing models for low-latency inference on embedded hardware.</li><li>Designing and building cloud-based training and labeling pipelines.</li><li>Collaborating with the hardware and embedded teams on sensor selection and vehicle packaging given safety requirements.</li><li>Writing performant, well-tested software, and improving code quality of the entire Autonomy team through code and design reviews.</li></ul><h3>What You'll Bring</h3><ul><li>5+ years of experience in software development for problems involving computer vision, machine learning, and robotic perception techniques.</li><li>Foundational understanding of deep learning: model layer design, loss function intuition, training best practices.</li><li>Experience handling large datasets efficiently and organizing them for training and evaluation.</li><li>Experience curating synthetic and real-world image datasets for training.</li><li>Strong proficiency in modern C++ and Python and experience writing efficient algorithms for resource-constrained embedded systems.</li><li>Ability to thrive in a fast-moving, collaborative, small team environment with lots of ownership.</li><li>Excellent analytical, communication, and documentation skills with demonstrated ability to collaborate with interdisciplinary stakeholders outside of Autonomy.</li><li>An eagerness to get your hands dirty by testing your code on real robots at real customer farms (gives “field testing” a whole new meaning!).</li></ul><h3>What Makes You a Strong Fit</h3><ul><li>Experience architecting multi-sensor ML systems from scratch.</li><li>Experience with compute-constrained pipelines: optimizing models to balance the accuracy vs. performance tradeoff, leveraging TensorRT, model quantization, etc.</li><li>Experience implementing custom operations in CUDA.</li><li>MS or PhD in Robotics, Computer Science, Computer Engineering, or a related field.</li><li>Publications at top-tier perception/robotics conferences (e.g. CVPR, ICRA, etc.).</li><li>Passion for sustainable agriculture and electric vehicles.</li></ul><br><div>Benefits:</div><div><br></div><div>• 100% covered medical, dental, and vision for the employee (cost plus partner, children, or</div><div>family is additional)</div><div>• Commuter Benefits</div><div>• Flexible Spending Account (FSA)</div><div>• Life Insurance</div><div>• Short- and Long-Term Disability</div><div>• 401k Plan</div><div>• Stock Options</div><div>• Collaborative work environment working alongside passionate mission-driven folks!</div><div><br></div><div>Our interview process is generally conducted in five (5) phases:</div><div><br></div><div>1. Phone Screen with People Operations (30 minutes)</div><div>2. Video Interview with the Hiring Manager (45 minutes)</div><div>3. Coding Challenge and Technical Challenge  (1 hour with an Autonomy Engineer)</div><div>4. Panel Interview (Video interviews scheduled with key stakeholders, each interview will be 30 to 45 minutes)</div><div>5. Final Interviews (CEO and CFO 30 minutes each)</div>

Software Engineer, Perception

About the Job

About the Company

Agtonomy

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