Scoutai

Scoutai

AI Cloud Infrastructure Engineer - Fury Team

Sunnyvale, CA · Full-time

Sponsorship not specified$160k-$240kDetected 113 days ago
PythonAWSGCPAzureCloud PlatformsDockerKubernetesPrometheusGrafanaMachine LearningPyTorchAirflowData EngineeringMLOpsAI OrchestrationSystems EngineeringElectrical EngineeringAdaptability

About the role

  • 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.
  • You'll be moving fast, context-switching daily, and helping define the culture and process as we go.

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

Requirements

  • 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)
  • 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
  • Deep understanding of data engineering (ETL pipelines, object storage, data versioning, metadata management)

Nice to have

  • Must be a U.S. Person due to required access to U.S. export controlled information or facilities
  • Work on the world's most important frontier, ensuring U.S. and allied dominance in the age of intelligent machines
  • 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

Compensation

  • 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.
  • US Salary Range
  • $160,000 - $240,000 USD

Benefits

  • Competitive compensation package including base salary and bonus.
  • Meaningful equity
  • Premium medical, dental, and vision plans with $0 paycheck contribution
  • Competitive PTO and company holiday calendar
  • 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.

Visa & Work Authorization

  • Must be a U.S. Person due to required access to U
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This listing is sourced directly from Scoutai's careers page and normalized into a canonical job model.