echoloc

Saildrone Tech Stack

Autonomous maritime systems for defense intelligence and ocean operations

Defense and Space Manufacturing Alameda, California 201–500 employees Privately Held

Saildrone builds uncrewed surface vehicles for military intelligence, surveillance, and maritime security in extreme ocean environments. The stack reflects a hardware-first, software-intensive operation: embedded Linux (Yocto, NXP i.MX8), real-time compute (NVIDIA Jetson, TensorRT), cloud infrastructure (AWS Lambda, SQS, Kubernetes), and classical control (Kalman filters). The hiring profile is engineering-dominant (16 roles) with acute manufacturing and supply-chain focus (4 manufacturing + 6 ops roles), matched against pain points in scaling production, electrical reliability, and meeting defense timelines—indicating a company transitioning from prototype to operational deployment.

Tech Stack 40 technologies

Core StackC++ Okta NetSuite Python TypeScript Go Greenhouse AWS AWS Lambda PostgreSQL Kubernetes Ansible gRPC Nvidia NXP i.MX8 Yocto Altium 365 Bazel macOS JumpCloud NX Altium C/C++ Bash NVIDIA Jetson TensorRT Kalman filter AWS SNS AWS SQS OAuth OIDC+10 more

What Saildrone Is Building

Challenges

  • Scaling manufacturing footprint
  • Ensuring system reliability
  • Operating in remote maritime environments
  • Eliminating build bottlenecks
  • Meeting mission timelines
  • Emi/emc blockers
  • Reliable long-duration maritime operations
  • Successful roadmap execution
  • Complex electrical failures across fleets
  • Maintaining production readiness for global deployments

Active Projects

  • Design and validation of electrical components for usvs
  • Global supply chain architecture
  • Standard costing transition
  • Quality management system implementation
  • Onboard software and networking infrastructure delivery
  • Embedded linux computer bring-up
  • Onboard software stack architecture
  • Development of complex pcbas
  • Validation strategy for maritime and defense standards
  • Autonomous maritime platform

Hiring Activity

Accelerating35 roles · 15 in 30d

Department

Engineering
16
Ops
6
Manufacturing
4
Finance
3
HR
1
Operations
1
Product
1
Security
1

Seniority

Senior
14
Mid
7
Staff
6
Manager
2
VP
2
Director
1
Junior
1
Company intelligence

Find more companies like Saildrone by tech stack, pain points and active projects

Get started free

About Saildrone

Saildrone designs and operates autonomous maritime platforms engineered for defense missions including persistent ISR, threat detection, and wide-area ocean intelligence. The product combines AI-driven autonomy, advanced sensor payloads, and long-duration renewable-powered endurance to operate in remote, hostile ocean environments. Core competencies span embedded systems (onboard software stack, Linux computer bring-up, complex PCB design), cloud-connected command and control, and validation against maritime and defense standards. The company is actively scaling manufacturing footprint and supply-chain architecture to support global defense deployments.

HeadquartersAlameda, California
Company Size201–500 employees
Hiring MarketsUnited States

Frequently Asked Questions

What tech stack does Saildrone use?

Embedded: C++, Yocto Linux, NXP i.MX8, Altium 365 (PCB design), NVIDIA Jetson, TensorRT. Cloud: AWS (Lambda, SNS, SQS), Kubernetes, PostgreSQL. Auth/ops: Okta, OAuth, OIDC, Ansible. Build: Bazel, NX.

Where is Saildrone headquartered?

Alameda, California. The company is privately held with 201–500 employees, currently hiring exclusively in the United States.

Similar Companies in Defense and Space Manufacturing

Other companies in the same industry, closest in size

How this profile is built

Saildrone's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.