At Laelaps AI, we believe robotics is entering a transformative decade, much like the arrival of the internet. Advances in AI, cloud computing, and hardware are reshaping what autonomous systems can do. Our mission is to build the intelligent software that powers physical security in the real world - enabling robots and sensors to handle dangerous and critical tasks that humans shouldn't have to. By engineering the orchestration layer for intelligent security, we aim to create a world that is safer, more secure, and more resilient.
We're a strong founding team based in Zurich, backed by visionary investors and advisors. We are engineering the future of security today!
As a Software Engineer on Robot Autonomy, you will build and own the state estimation that tells our robots how they are moving and where they are. You'll fuse data from IMUs, cameras, LiDAR, GNSS, and platform-specific odometry into accurate, real-time estimates that support reliable autonomy day and night, across different robot platforms.
This is a builder's role first: you'll use the estimation methods and tools best suited to the problem, then do the engineering needed to make them work on real robots. Our robots operate in complex environments where terrain, weather, vibration, lighting, and sensor dropouts degrade measurements. We care less about novelty for its own sake and more about whether your systems perform reliably across platforms in the field.
Design and ship real-time estimators for position, orientation, velocity, and angular velocity across our robot platforms.
Fuse data from multiple sensors, handling noise, asynchronous measurements, calibration errors, changing sensor quality, and dropouts.
Develop estimation approaches suited to different platforms, including reusable components and interfaces that account for their distinct sensors and dynamics.
Improve localization and odometry in challenging conditions, including GNSS-denied environments and cases with degraded or intermittent sensing.
Integrate state estimation with perception, planning, and control so downstream systems receive reliable estimates and useful uncertainty information.
Investigate failures using logs, datasets, simulation, and field testing; identify root causes and verify that fixes improve performance on real robots.
Build evaluation and testing workflows that make estimator performance measurable and repeatable across robot types and operating conditions.
Work closely with the rest of Robot Autonomy and with forward-deployed engineers to turn deployment experience into improvements to the estimation stack.
We're looking for an engineer who has built or deployed state estimation systems for real robotic or autonomous platforms. You understand that estimator performance depends on the whole system: sensor behavior, calibration, timing, platform dynamics, and how autonomy uses the estimate.
You're comfortable choosing an approach based on the operational need, then making it robust through careful implementation, evaluation, and field validation. You measure success by whether robots operate reliably in the real world, not by algorithmic novelty alone.
A Master's degree or PhD in mechanical engineering, computer science, robotics, electrical engineering, or a related field, or equivalent practical experience.
Proven experience building or deploying state estimation, localization, or odometry systems for robots or autonomous systems (3+ years or equivalent depth).
Strong understanding of nonlinear state estimation, sensor fusion, Kalman filtering, and uncertainty representation.
Experience working with real sensor data and practical issues such as noise, calibration, synchronization, vibration, and data loss.
Strong C++ and Python skills, with experience building robotics software in ROS 2.
Ability to analyze estimation failures and debug issues across sensors, software, and robot behavior.
Experience evaluating robotics systems using recorded data, simulation, or physical robots.
Strong software engineering practices, including version control, reproducible experiments, and disciplined performance evaluation.
Experience with both ground and aerial robots, or with applying estimation methods across different robot platforms.
Experience with visual-inertial odometry, LiDAR-inertial odometry, SLAM, or GNSS/INS integration.
Familiarity with optimization-based estimation and factor graph tools such as GTSAM or Ceres.
Understanding of robot dynamics and how estimation affects planning and control.
Experience operating robots in challenging conditions such as GNSS-denied areas, low light, dust, rain, or high vibration.
Experience monitoring or improving deployed robotics systems in the field.
Publications at top robotics venues are a plus, but not expected. We value reliable systems shipped on real robots.
Ownership: you are able to ship products and deliver project end-to-end.
Mission: autonomous security that keeps people and critical sites safe, including in defence.
Career path: a ground-floor seat with real runway. Prove your value and you will not have barriers to grow.
Team: work directly with PhD-level co-founders in AI, Robotics, and Physics, alongside a strong (and fun) founding team.
Compensation: Competitive equity/salary package
Culture: International founding team that is serious about building but does not take itself too seriously.
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