Senior Robotics Software Engineer

Anduril Industries

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Quick summary

Work type
On-site
Location
Waltham, MA
Salary
$191,000–$253,000 / yr
Posted
4 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $187k
This role $222k
$124k most similar roles pay here $267k

This role pays more than 77% of similar roles. Most pay $152,307–$222,000 — the shaded band above. At the midpoint, this role pays about $222k versus about $187k for comparable roles.

Based on 240 similar postings.

Employer

About Anduril Industries

Anduril Industries is a defense technology company that builds advanced hardware and software systems for national security, including autonomous drones, surveillance systems, and the Lattice AI command platform.

Anduril Industries currently has 884 open roles on FindRole.

Listed pay typically runs $166,000–$220,000 across 854 roles with salary data.

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At a glance

TL;DR · Senior Robotics Software Engineer

As a Senior Robotics Software Engineer on the Battlespace Awareness Command and Control Software team, you will develop high-performance software for real-time command and control systems deployed on operational platforms. You will prototype and deploy state-of-the-art algorithms for global and local path planning, trajectory optimization, and multi-agent coordination to manage fleets of unmanned systems in dynamic, contested environments. Your daily work involves building robust, concurrent code for autonomous tasking and routing services while ensuring reliable execution in resource-constrained settings. You will utilize C/C++ or Rust to implement search algorithms like A* and RRT*, leveraging expertise in guidance, navigation, and control, as well as linear algebra and computational geometry. The role addresses the technical challenge of providing automated route optimization and obstacle avoidance for ground, air, and maritime platforms within a distributed command and control architecture.

What you'll do

  • Prototype and deploy algorithms for global/local path planning, trajectory optimization, and multi-agent coordination.
  • Develop real-time path planning capabilities that adapt to changing mission conditions and threats.
  • Build high-performance C2 software using asynchronous programming and concurrency in resource-constrained environments.
  • Implement robust search algorithms and decision-making systems for navigation in dynamic, contested environments.
  • Analyze system performance through high-fidelity simulations and statistical modeling to validate planner behavior.
  • Develop mission-critical features including collaborative autonomy, asset routing, and obstacle avoidance.
  • Integrate path planning technologies into the full software stack from requirements to production optimization.
  • Translate technical progress into actionable insights for stakeholders, operators, and end-users.

What we're looking for

  • 8+ years of experience in algorithm design, software development, and mathematical modeling using C/C++ or Rust.
  • Strong knowledge of path planning techniques including graph-based search, sampling-based planners, and real-time replanning.
  • Experience in guidance, navigation, and control (GNC), trajectory optimization, and predictive models for vehicle dynamics.
  • Solid understanding of applied mathematics including linear algebra, optimization, computational geometry, and graph theory.
  • Knowledge of vehicle dynamics, kinematic constraints, and control theory for autonomous ground, air, or maritime platforms.
  • Familiarity with map representations, terrain reasoning, state estimation, and large-scale geospatial data handling.
  • Exposure to machine learning as applied to planning and decision-making, including reinforcement learning and behavior prediction.
  • Eligible to obtain and maintain an active U.S. Secret security clearance.
  • Experience with Rust for high-performance, safety-critical software (preferred).
  • Experience with mixed greenfield/brownfield codebases and extending existing production stacks (preferred).

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