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Our Mission

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!

THE ROLE

As a Software Engineer on Robot Autonomy, you will make our robots navigate dependably across real customer sites. Our stack works. The gap between working and dependable is the whole job. Every new site tests how a robot understands its surroundings and chooses where to go: a ramp the planner avoids, a narrow passage that exposes a poor route, a gate that changes the map, a person who steps into the robot's path, or localization drift that builds over a long patrol. You treat those cases as the real navigation problem to solve, not as edge cases.

You'll shape the technical choices behind reliable navigation, from sensor selection, ground segmentation, and traversability estimation to predicting how people and vehicles move and planning safe, efficient routes around them. The system has to work day and night, in challenging weather, across different embodiments and changing site conditions. We measure success by whether the robot completes its patrol on a live site, not by how it performs in simulation.

WHAT YOU'LL WORK ON

• Navigation and path-planning design: how robots represent traversable space, select routes, avoid obstacles, and reach goals across complex sites.

• Sensor integration driven by navigation requirements, including what ground segmentation and traversability estimation need in day, night, and challenging weather.

• Environment understanding: how the robot distinguishes ground from obstacles and estimates which terrain is safe and practical to traverse.

• Behavior prediction: anticipate how people, vehicles, and other dynamic obstacles will move, and plan routes that stay safe and efficient around them.

• Field reliability: reproduce failures from deployments, find the root cause, and fix it at the right layer, from sensor data and maps to costmaps, planners, and recovery behaviors.

• Planning under imperfect localization: plans that stay useful when the state estimate drifts and the robot must execute routes in tight or dynamic environments, working with the rest of Robot Autonomy on localization and control.

• Validation on real robots: logs, simulation, and repeatable field tests to verify that design choices and changes hold across routes, lighting, weather, and site layouts.

• New autonomy capabilities: work with the engineers building the operator application and backend so operator requests and new robot capabilities rest on a sound navigation design.

• The field feedback loop: work closely with forward-deployed engineers to turn site issues into bugs, design changes, and improvements to the navigation stack.

• Regular site visits to build a practical understanding of how robots and sensors behave in real operating conditions.

WHO WE'RE LOOKING FOR

We're looking for an engineer who has taken a robotics system from unreliable to dependable and takes ownership beyond individual tickets. You can explain why you made a navigation design choice and what it costs. When a robot takes a bad route, you can tell whether the planner, the map, the state estimate, or the robot's behavior is at fault, and you fix the right one. You are comfortable in the field and want to understand how robots behave in real customer environments.

YOUR BACKGROUND:

• A Master's degree or PhD in mechanical engineering, computer science, robotics, electrical engineering, or a related field, or equivalent practical experience.

• Proven track record building and deploying navigation on ground mobile robots in the real world (3+ years or equivalent depth).

• Hands-on experience with mobile robot navigation and path planning: route or local planning, static and dynamic obstacle avoidance, costmaps, or recovery behaviors.

• Understanding of how mapping and localization affect navigation, and the ability to diagnose when a planning issue is actually caused by the map, the state estimate, or robot behavior.

• Understanding of how lighting, weather, terrain, and sensor limitations affect perception and navigation, with experience developing or validating systems for demanding real-world conditions.

• Hands-on experience with robotics sensors and hardware, especially LiDAR, IMUs, and cameras. You can investigate issues across software, networking, and hardware boundaries.

• Experience testing and debugging navigation on physical robots using logs, visualization, simulation, and repeatable field tests.

• Strong ROS 2, C++, and Python skills.

• Clear communication of navigation and path-planning design choices and their trade-offs.

• Willingness to visit customer sites regularly.

NICE TO HAVE:

• Experience with legged robots or with more than one robot embodiment.

• Experience with Nav2 or a comparable navigation framework.

• Motion prediction or planning among people and vehicles, such as trajectory forecasting or socially aware navigation.

• Terrain mapping and traversability methods: elevation mapping, learned traversability, or semantic segmentation for navigation.

• Experience with night-time or all-weather sensing, such as thermal cameras or LiDAR in rain and fog.

• Background in security, defence, or other safety-critical robotics deployments.

What We Offer

• 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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Our Mission

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!

THE ROLE

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.

WHAT YOU'LL WORK ON

• 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.

WHO WE'RE LOOKING FOR

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.

YOUR BACKGROUND:

• 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.

NICE TO HAVE:

• 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.

What We Offer

• 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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Our Mission

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!

THE ROLE

As a Reinforcement Learning Intern on Robot Autonomy, you'll train locomotion and low-level control policies for our legged security robots and help take them from simulation to real hardware. You'll work close to the actuators, from joint-level behavior through coordinated locomotion, on robots that patrol outdoor sites across varied terrain and challenging weather.

This role is highly practical: you'll design training setups, run experiments in simulation, transfer policies to physical robots, and measure how they hold up. You'll get hands-on experience with the gap between a policy that works in simulation and one that keeps a robot on its feet on wet ground at night.

WHAT YOU'LL WORK ON

• Train and evaluate reinforcement learning policies for locomotion and low-level control in simulation.

• Apply sim-to-real techniques such as domain randomization, reward design, and policy robustness methods, and test the results on physical robots.

• Make policies robust to varied terrain, challenging weather, and noisy, delayed, or missing sensor data.

• Explore control approaches that transfer across robot embodiments with different actuators and dynamics.

• Build evaluation workflows with clear metrics and repeatable experiments, in simulation and on hardware.

• Apply solid engineering practices: experiment tracking, version control, reproducible training runs.

WHO WE'RE LOOKING FOR

We're looking for a motivated robotics or machine learning student excited to apply academic training in a fast-moving startup. You'll be surrounded by a team that values learning, experimentation, and building things that actually work in the real world.

YOUR BACKGROUND:

• Currently pursuing a PhD or recently completed a Master's degree in Robotics, Machine Learning, Computer Science, or a closely related field.

• Hands-on experience training reinforcement learning policies for robot control, in simulation or on hardware.

• Experience with robotics simulators such as Isaac Sim, MuJoCo, or Gazebo.

• Solid grounding in robot dynamics and control.

• Good coding skills in Python, with PyTorch (or JAX).

• Comfortable using Docker and Git in your workflows.

NICE TO HAVE:

• Experience deploying learned policies on physical robots, ideally legged.

• Experience with low-level actuator, motor, or joint control.

• C++ and ROS 2 experience.

• Publications at top robotics or ML venues (CoRL, RSS, ICRA, NeurIPS).

What We Offer

• 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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Technology that speaks your language

Domera Labs builds Ami, the first AI companion for seniors. Ami brings the power of a smartphone into a more human form: voice-first and deeply personalized

We at Domera Labs are rethinking human-machine interaction from first principles by introducing a better interface to interact with technology: voice

By combining the most intuitive hardware design with frontier AI, Ami makes AI accessible for the fastest growing demographic worldwide. The goal is to make the everyday life older adults more seamless, while addressing that generation's biggest challenge: loneliness and isolation. With Ami we are building the category leader of a new hardware paradigm by building a full standalone device (and not a gadget) that aims to makes the smartphones of today redundant.

The underlying technology of Ami combines a model-agnostic streaming pipeline consisting of proprietary models and off-the-shelf frontier models to create a hyper-personalized and proactive user experience. The backbone of Ami is built by our foundational lab that builds a social intelligence model that is optimized for social interaction, human behavior and interpersonal skills.

Domera Labs has secured large distribution agreements, a model co-development partnership with a leading AI lab, and ODM manufacturing proposals. We are looking for people who want to build at the intersection of human-machine interaction, mass-consumer facing hardware and shape frontier research with social/non-quantifiable benchmarking.

Core Responsibilities

You own the software that makes Ami work. Your primary responsibility is to architect, write and ship the on-device application and services for our mass-market consumer device, from voice interaction and cloud connectivity to onboarding, recovery and everyday reliability. You will work directly with our ODM and silicon partners to integrate that software with the underlying platform.

Our target hardware uses a Qualcomm SoC with Android/AOSP or embedded Linux depending on the final platform selection.

Our users are 75 years old and there is no screen, no settings menu, and no IT support. If the device does not work out of the box, it fails. Your job is to make the following work.

• On-device application: build and own Ami's application and services, including interaction logic, real-time audio streaming, cloud communication, local state and recovery from network interruptions or service failures

• Device identity and fleet management: provisioning, unique device identity, secure key storage, and the systems that let us know what every unit in the field is doing

• The maintenance channel: a reliable service and diagnostics path to the device (BLE, USB-C, or both) for field debugging, factory test, and recovery

• Out-of-the-box experience: first-boot network onboarding that a senior can complete alone, with no screen and no smartphone as a crutch. This is the single highest-stakes piece of the product

• Flash and update management: partition layout, A/B OTA with rollback, staged fleet rollouts, and bricking as a category of bug that never happens

• Base platform behaviors: boot and recovery, factory and soft resets, button and LED mappings, audio feedback, power states and battery behavior

• The audio front end: working with our ODM and silicon partners on mic array, echo cancellation, wake word, and the latency budget from mic to first spoken token

• Bringing the device through EVT, DVT, and PVT with our ODM as the technical counterpart on our side

What we are looking for

• ⁠A builder's mindset: ship > fail > learn > improve

• Stay focused when multiple priorities compete and the ranking is unclear

• Work seamlessly across research and engineering

• Can navigate ambiguity and make progress in fast-moving research environments

• This is a founding-level position. You will work directly with the founders, shape the architecture from the ground up, and see your work in users' hands within months, not years.

Technical Requirements

• You have shipped a connected consumer device to production, not just to a demo table. You know what goes wrong between DVT and mass production

• Strong hands-on experience building production device applications and services on Android/AOSP, using Kotlin or Java and C/C++ for native components and hardware integration. You can own the on-device application end to end, including background execution, connectivity, audio and integration with platform services. Experience with embedded Linux is a plus; Python proficiency for tooling and testing is expected.

• Experience developing for AOSP-based devices beyond standard smartphone apps: integrating privileged applications and services, working with system permissions and hardware interfaces, and collaborating with an ODM or silicon vendor on the underlying platform. Qualcomm platform experience is a plus.

• Wireless connectivity in the real world: Wi-Fi provisioning, BLE, and ideally cellular. You have debugged a device that would not join a network in someone's home

• OTA and flash: bootloaders, secure boot, A/B partitioning, rollback, and staged rollouts across a fleet

• You can diagnose issues across application code, platform services and hardware interfaces

• A builder's mindset: you'd rather ship and measure than debate

• Bonus: real-time audio pipelines (I2S, DSP, AEC, wake word), on-device ML inference, factory test and manufacturing line bring-up, regulatory certification (CE, FCC), power optimization for battery life, experience in NLU / NLP

We lean toward senior engineers who can independently own production device software, but demonstrated ownership matters more than years of experience. Experience integrating real-time AI services into a consumer product is a plus.

What you get

• ⁠Founding-team equity and a real say in technical direction

• ⁠A product with signed launch partners, not a demo in search of a market

• ⁠A small team, short decision paths

• Cash compensation range of CHF 80 - 120k with significant equity incentives

• Opportunity to shape the future of hardware and social intelligent AI models

We encourage you to apply even if you do not believe you meet every single qualification.

Compensation: CHF 70K – CHF 120K • Offers Equity

• • Estimated base salary CHF 70K – CHF 120K • Offers Equity

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