AI Cloud Infrastructure Engineer

The future of defense will be decided by those who field intelligent machines at scale. At Scout AI, we’re developing Fury, the first robotic foundation model for defense, to give U.S. forces overwhelming, adaptable, and autonomous power across every domain. Fury enables human operators to command fleets of robots through natural language, and empowers those machines to sense, decide, and act together as one. This mission will ask everything of us: urgency, precision, and relentless work. The Role We’re looking for an AI Infrastructure Engineer to build and scale the backbone of Fury’s model training and deployment ecosystem. You’ll design the data, compute, and orchestration infrastructure that enables our vision-language-action models to learn from massive real-world datasets and operate across edge and cloud environments. This role bridges systems engineering, distributed computing, and machine learning infrastructure. Your work will ensure our teams can iterate rapidly, train large models efficiently, and deploy them reliably on robotic platforms in the field. We’re a startup. You’ll be moving fast, context-switching daily, and helping define the culture and process as we go. This is a rare opportunity to come in early and architect the future of defense. Scout AI prefers in-office work but will consider hybrid or remote arrangements for key contributors. Responsibilities
Design and implement data pipelines for ingesting, transforming, and storing petabytes of multimodal data from Fury’s robotic and operator systems
Develop internal tooling for dataset exploration, curation, versioning, and quality monitoring over time
Build and maintain distributed training infrastructure (cloud and on-prem) for large-scale multimodal and foundation model training
Implement job orchestration workflows for launching, tracking, and debugging large-scale model runs
Identify and remediate bottlenecks in compute, memory, storage, and network performance to optimize throughput and cost efficiency
Collaborate with AI, autonomy, and systems teams to ensure data and training infrastructure supports real-time and mission-critical use cases
Maintain observability and reliability tooling for training and inference pipelines
Stay current on best practices in MLOps, distributed training frameworks, and AI infrastructure at scale Qualifications
3+ years of experience in ML infrastructure, MLOps, or large-scale data systems
Proven experience with distributed training (PyTorch DDP, DeepSpeed, Ray, or similar) and workflow orchestration (Kubernetes, Airflow, or equivalent)
Strong proficiency in Python and cloud-native infrastructure (AWS, GCP, or Azure)
Deep understanding of data engineering (ETL pipelines, object storage, data versioning, metadata management)
Familiarity with containerization and deployment (Docker, Kubernetes) and monitoring systems (Prometheus, Grafana)
Experience optimizing GPU cluster utilization, scaling training jobs, and profiling model performance
Bachelor’s degree or higher in Computer Science, Electrical Engineering, or related technical field
Bonus: Experience with edge-deployed ML systems, federated training, or robotic data collection pipelines
Must be a U.S. Person due to required access to U.S. export controlled information or facilities Why Join Scout
Work on the world’s most important frontier, ensuring U.S. and allied dominance in the age of intelligent machines
Be a core part of a team building the first defense-specific robotic foundation model
Collaborate with some of the top engineers in autonomy, AI, and national security
See your work deployed on real systems
Help define the future of intelligent defense systems
Backed by Draper Associates, Booz Allen Ventures, and other top investors Benefits
Competitive compensation package including base salary and bonus.
Generous equity participation in company growth.
Premium medical, dental, and vision plans with $0 paycheck contribution
Competitive PTO and company holiday calendar
Catered lunch daily and fully stocked kitchen
EV charging
Relocation assistance (depending on role eligibility) The stated salary range below represents an estimated base pay only and reflects consideration of multiple compensation factors. Final salary offers may differ depending on factors including, but not limited to, relevant experience or training background, specialized skills, and business needs. Most full-time positions also include highly competitive equity awards, which form part of Scout AI's overall compensation package. In addition, Scout AI provides comprehensive, top-tier benefits to full-time employees. US Salary Range $160,000 - $240,000 USD