AI Infrastructure Supply Chain Lead

About the Role

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.

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. 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.

This role is office‑based at our Bellevue, Washington office.

• 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.

• 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.

• 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 skills with a bias for action.
• Strong time‑management and organization skills to thrive in a fast‑paced, dynamic environment.
• Solid written and oral communications skills.
• Good teamwork and interpersonal skills.

For U.S. based candidates:
To ensure fairness and transparency, the starting base salary range for this role is $154,560—$193,200 USD, varying based on location, experience, skills, and qualifications.

In addition to base salary, this role will also be offered equity and subsidized benefits (details available upon request).

• Competitive…