About the role
We’re Blue River, a team of innovators driven to create intelligent machinery that solves monumental problems for our customers. We empower our customers – farmers, construction crews, and foresters - to implement safer and more sustainable solutions, driving increased profitability with less reliance on scarce labor. We believe that focusing on the small stuff – pixel-by-pixel and task-by-task - leads to big gains. Blue River Technology aligns with John Deere’s vision to “innovate on behalf of humanity” by quickly identifying and solving high-value, high-uncertainty challenges in AI, machine learning, computer vision, and robotics. BRT acts as a research and development flywheel, building not only new products but also new platforms that reliably create value for both Deere and its customers. From fully autonomous machines to highly precise farming equipment, BRT and Deere are partnering to create technical breakthroughs in industries like agriculture and construction. Our people are at the heart of what we do. Through cross-disciplinary collaboration, this mission-driven team is eager to define the new frontier of robotics. We are always asking hard questions, rapidly iterating, and getting our boots in the field to figure it out. We won’t give up until we’ve made a tangible and positive impact on the planet! Blue River Technology is based in Santa Clara, CA. Summary We are seeking a motivated Senior CVML Engineer for Blue River Technology's autonomous mower initiative. You will be responsible for developing core computer vision models to enhance system safety and performance in challenging production environments. This role spans the entire development lifecycle, from initial prototyping to production scaling, including data collection, model training, and model deployment on embedded systems. We are looking for an experienced, collaborative individual eager to contribute to the future of autonomous mowing. Employment Type : Full-Time Work Location : Remote in the United States Visa sponsorship : Open to visa sponsorship. Job
Responsibilities A combination, not necessarily all-inclusive, of the following: Build production models. You will design, train, and deploy production-grade deep learning models for critical perception tasks of depth estimation, segmentation, and tracking. Advanced Edge optimization. You will fine-tune models for real-time, sub-millisecond inference on the mower’s embedded NVIDIA GPU platforms. You will design custom mixed-precision strategies and implement quantization-aware training for model attention layers. Own model development. You’ll take complete ownership of your models, from rapid prototyping through to validation and final deployment in the perception pipeline. System integration. You will collaborate closely with our robotics team to integrate perception outputs into the robotics stack. You will architect onboard pipelines, maximizing GPU saturation across multiple camera feeds. Data-driven improvement. You will analyze performance on mowing site data, identify failure cases, and continuously improve the model and perception pipeline’s performance against challenging outdoor conditions. Leverage real and synthetic data. You will develop strategies for using real-world site data and generating synthetic data to train models and validate the perception pipeline’s performance, thereby improving overall system robustness. Required Experience and Skills Bachelor’s or Master’s Degree in Computer Science or a related field, graduate degree preferred. 5+ years of post-academic experience building and deploying production vision models on real-time embedded systems. Hands-on expertise with deep learning frameworks (PyTorch preferred) and a deep understanding of modern computer vision architectures. Proven track record of taking models through advanced optimization pipelines with strong proficiency in TensorRT, NVIDIA ModelOpt, and ONNX runtime. Strong Python programming skills for model development and a strong command of C++ for writing performance-critical code. Preferred Experience and Skills Direct experience deploying real-time vision models on physical robots or autonomous vehicles. Demonstrated ability to build and deploy end-to-end ML pipelines (data ingestion, training, testing, and deployment). Proficiency with on-device model optimizations using TensorRT, ONNX, or similar engines. Experience with hardware-accelerated compression techniques, knowledge distillation, or network structural pruning. Familiarity with robotics frameworks like ROS / ROS2. At Blue River, your base pay is one part of your total
