AI Engineer

About the role

Armada is a full-stack edge infrastructure company delivering compute, connectivity, and sovereign AI/ML to some of the world's most remote places. Named one of Fast Company's Most Innovative Companies, Armada's solutions are deployed in over 60 countries globally for organizations ranging from energy to defense. With over $200 million in funding, Armada is backed by top investors such as Microsoft (M12), Founders Fund, and has strategic partnerships including Starlink, Skydio, and NVIDIA. We are looking for the most brilliant minds in the world to join us. Working at Armada means taking ownership, driving autonomy, and delivering impact. You'll tackle challenges that haven't been solved before and help build something transformative from the ground up. What you do here will not only define your career but help further Armada's mission to bridge the digital divide for customers around the world. At Armada, we are unlocking the limitless potential of AI to transform operations and improve lives in some of the most remote locations on Earth. From the expansive mines of Australia to the oil fields of Northern Canada, and the coffee plantations of Colombia, Armada offers a unique opportunity to tackle exciting AI and ML challenges on a global scale. We are actively seeking passionate AI Engineers with hands-on expertise across a range of domains, including real-time computer vision, statistical machine learning, natural language processing, transformers, control and navigation, reinforcement learning, and large-scale distributed AI systems. Ideal candidates will possess strong skills in machine learning (ML), deep learning (DL), and real-time computer vision techniques. You will be responsible for building ML/DL models tailored to specific challenges, preparing datasets for testing, evaluating model performance, and deploying solutions in production environments. Familiarity with containerization, microservices architecture, and the ability to independently deploy ML models into production is essential. If you are a self-driven individual with a passion for cutting-edge AI, we want to hear from you. Armada offers an unparalleled opportunity to confront some of the most thrilling AI and ML challenges in the world. Join our dynamic AI Engineering team as we deliver disruptive edge-compute systems capable of autonomous learning, prediction, and adaptation using vast, real-time datasets. We are pioneers in developing high-performance computing solutions for self-driving cars, camera networks, robotics, drones, conversational agents, and real-time monitoring and diagnostic systems. Our vision is to empower AI systems to seamlessly and securely interact with the complexities and uncertainties of the real world, and our mission is to bridge the digital divide in the process. Location. This role is office-based at our Bellevue, Washington office. What You'll Do (Key Responsibilities) Translating business requirements into requirements for AI/ML models. Preparing data to train and evaluate AI/ML/DL models. Building AI/ML/DL models by applying state-of-the-art algorithms, especially transformers. In some cases, leverage existing algorithms from academic or industrial research. Testing, evaluating the AI/ML/DL models, benchmarking their quality, and publishing the models, data sets, and evaluations. Deploying the models in production by containerizing the models. Working with customers and internal employees to refine the quality of the models. Establishing continuous learning pipelines for models with online learning or transfer learning. Building and deploying containerized applications on the cloud or on-premise environments Required Qualifications BS or MS degree in computer science, computational. science/engineering, or related technical field (or equivalent experience). 3+ years of work-related experience in software development with good Python, Java, and/or C/C++ programming skills. Familiarity with containers, numeric libraries, modular software design. Hands-on expertise with traditional statistical machine learning techniques as well as deep-learning and natural language processing modeling. Expertise in supervised, unsupervised, and transfer learning techniques. Hands-on expertise in machine learning techniques and algorithms with a strong background in state-of-the-art DNN architectures (Transformers, CNN, R-CNN, RNN, BERT, GAN, autoencoders, etc.) and experience in developing or using major deep learning frameworks (e.g., PyTorch, Tensorflow, etc). Experience with solving and using machine learning for real-world problems. Preferred Experience and Skills Demonstrable experience in building, programming, and integrating software and hardware for autonomous or robotic systems. Proven experience producing computationally efficient software to meet real-time requirements. Background with container platforms such as Kubernetes. Strong analytical ski

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