1.52 Robotics Autonomy Engineer - Reasoning

Field AI-posted 4 months ago
$70,000 - $200,000/Yr
Full-time • Mid Level
Irvine, CA
11-50 employees
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At Field AI, we’re building robots that don’t just sense the world, they reason about it and make intelligent decisions in real time. As a Robotics Autonomy Engineer - Reasoning, you’ll design and deploy scalable, interpretable world models and decision-making systems that let our robots operate safely and intelligently in dynamic, uncertain environments. You’ll fuse multi-modal sensing with semantics and risk analysis, enable real-time decision-making under uncertainty, and embed transparency, adaptability, and fail-safes into the autonomy stack. This is a role for an engineer who thrives at the frontier of AI and robotics—someone excited to push beyond perception into true reasoning, and to see their work come alive in robots that adapt and succeed in the real world.

  • Design and iterate on scalable, interpretable spatio-temporal-semantic world models.
  • Fuse multi-modal sensing with semantics and embedded risk analysis.
  • Ensure real-time performance with low latency in dynamic, uncertain environments.
  • Develop reasoning and decision-making systems that remain reliable under uncertainty and enable success in complex real-world missions.
  • Validate reasoning systems across challenging edge-case scenarios (e.g., sudden obstacles, degraded sensing).
  • Integrate reasoning with perception and control for closed-loop autonomy at high mission success rates.
  • Implement diagnostic layers that log reasoning steps for interpretability and post-mission analysis.
  • Develop fail-safe behaviors that trigger under uncertain or conflicting world-state estimates.
  • Ensure adaptability to new environments while always prioritizing safety.
  • Master’s degree or higher in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related field, with focus on autonomy, reasoning, or decision-making.
  • Strong foundation in algorithms for reasoning and decision-making under uncertainty (e.g., probabilistic methods, motion planning, decision theory, foundation models).
  • Demonstrated experience building and deploying autonomy systems in simulation and/or real-world robotic platforms.
  • Proficiency in modern machine learning techniques relevant to robotics (e.g., reinforcement learning, foundation models, representation learning).
  • Strong software engineering skills in C++ and Python, with experience developing real-time robotics or AI systems.
  • Track record of research contributions (e.g., publications, open-source projects) or demonstrated ability to advance state-of-the-art methods into practical systems.
  • Background in semantic reasonings, human-robot interaction, or multi-agent system.
  • Familiarity with ROS or similar middleware for robotics development and deployment.
  • Knowledge of hardware-aware optimization and acceleration of autonomy stacks (e.g., real-time constraints, GPU/TPU programming).
  • Experience deploying autonomy on physical robotic platforms in real-world field environments (e.g., outdoor, off-road, degraded sensing).
  • Generous salary range ($70,000 - $200,000 annual), with consideration of individual background and experience.
  • Open to exploring a hybrid or remote work option.
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