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WHO WE ARE AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com http://www.aerovect.com. YOU WILL • Architect 3D object detection models, including multi-modal approaches (camera, LiDAR, Radar). • Build and maintain data collection and evaluation (metrics) pipeline. • Develop a proprietary multi-modal dataset for training and evaluation. • Train, deploy and monitor 2D/3D object detection models to production. • Build and execute a roadmap for the perception system • Mentor junior engineers about best practices. YOU HAVE • Master’s or PhD in Computer Science, Robotics, Deep Learning, or a related field. • 7+ years of focused experience in architecting and deploying 2D/3D object detection models. • Worked on entire perception stack (sensing, preprocessing, detection & tracking) • Python proficiency • The ability to identify gaps and lead cross functional projects WE PREFER • PhD in Computer Science, Robotics, or a related discipline • Full stack AV knowledge • Experience in architecting perception systems (detection & tracking) • Publications in major conferences like CVPR, ICRA, NeurIPS, IJCAI, AAAI etc

WHO WE ARE AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com http://www.aerovect.com. JOB DESCRIPTION We are looking for an experienced Staff Software Engineer who can design and build best-in-class planning systems for autonomous driving in structured, low-speed environments. In this role, you'll be the technical backbone of the planning stack — owning the design and implementation of production-grade mission planning, behavior planning, and motion planning software. You'll work across the full planning pipeline to achieve category-defining vehicle autonomy for the airside, tackling hard problems in trajectory optimization, decision-making under uncertainty, and real-time constraint optimization. This opportunity offers a deeply technical engineer the chance to shape a market-defining enterprise product that combines autonomous vehicle technology with a robotics-as-a-service (RaaS) business model. This role reports to our Planning Tech Lead and works closely with the autonomy engineering team. You Will: • Design, implement, and iterate on the mission planner, behavior planner, and motion planner for autonomous ground support equipment operating in airport airside environments. • Drive key technical decisions across the planning stack — selecting algorithms, defining interfaces, and establishing the architecture that the team builds on. • Prototype and evaluate new planning approaches (e.g., optimization-based methods, search-based planners, learning-augmented pipelines) and bring the best ideas to production. • Collaborate cross-functionally with perception, controls, localization, and systems engineering teams to deliver an integrated autonomous driving system. • Establish and promote best practices in software development, functional safety, and systems engineering as they apply to the planning domain. • Mentor other engineers through technical guidance, code review, and design discussions. You Have: • Bachelor's or Master's degree in Computer Science, Math, Electrical Engineering, Mechanical Engineering, Robotics, Physics, or a related field. • Extensive hands-on experience designing and implementing planning modules for autonomous systems shipped to production or deployed in real-world operations. • Strong programming skills in C++ (preferred) or Python, and experience with Linux-based operating systems. • Demonstrated ability to take ambiguous technical problems and drive them to well-architected solutions independently. • Excellent communication skills, proactiveness, and a strong sense of ownership. We Prefer: • MS or Ph.D. in Computer Science, Robotics, or a related field. • Mastery of Modern C++ (14 and beyond) and safety-critical coding practices (e.g., MISRA, ISO 26262). • 5+ years of industry experience in planning for robotic ground vehicles. • In-depth understanding of DDS frameworks like ROS/ROS2 or other networking middleware. • Experience in startup environments, demonstrating adaptability to rapidly changing priorities.

WHO WE ARE AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com http://www.aerovect.com. We are looking for an experienced Senior Software Engineer who can design and build best-in-class behavior planning systems for autonomous driving in structured, low-speed environments. In this role, you'll own the design and implementation of key modules in the behavior planner — the decision-making layer that determines what the vehicle should do in complex, dynamic airside scenarios. You'll work at the intersection of mission-level goals and motion-level execution, tackling problems in multi-agent interaction modeling, rule-based and learned decision-making, and robust handling of edge cases unique to airport ground operations. This opportunity offers a deeply technical engineer the chance to shape a market-defining enterprise product that combines autonomous vehicle technology with a robotics-as-a-service (RaaS) business model. This role reports to our Planning Tech Lead and works closely with the autonomy engineering team. YOU WILL • Develop and implement advanced behavior planning algorithms for autonomous vehicles • Collaborate with cross-functional teams to ensure robust integration and functionality of planning systems • Design, write, and maintain efficient and scalable code in C++ and Python • Contribute to the architecture and continuous improvement of behavior planning software • Conduct extensive testing in simulated environments and real-world scenarios to validate and refine behavior planning algorithms • Analyze system performance and implement enhancements based on data and feedback • Maintain comprehensive documentation of code, algorithms, and system designs • Work closely with other engineering teams to ensure seamless coordination and development YOU HAVE • Proficient in modern C++ (11/14/17) and object-oriented programming • Skilled in Python for rapid prototyping and testing • Strong in debugging, profiling, and optimizing code • Deep understanding of behavior planning algorithms such as state machines, behavior trees, and probabilistic planning • Familiarity with path planning algorithms like A*, RRT, or optimization-based methods • Master’s degree in Computer Science, Robotics, or a related field • Minimum of 3 years of industry experience in autonomous driving, robotics, or a related field WE PREFER • Knowledge of state machines, behavior trees, and decision-making under uncertainty • Expertise in path planning algorithms such as A, D, and Rapidly-exploring Random Trees (RRT) • Knowledge of machine learning techniques, especially in the context of behavior prediction and planning • Experience with ROS / ROS2 • Implementing systems that can re-plan at high frequencies to adapt to dynamic changes in the environment • Ensuring that behavior planning algorithms can execute with minimal latency for real-time navigation • Proficiency in optimization techniques and probabilistic models for making informed planning decisions under uncertainty • Master’s degree or PhD in Robotics, AI, Mathematics, or a related field with a focus on planning, optimization, or control theory is a plus

WHO WE ARE AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com http://www.aerovect.com. We are looking for a Staff Software Engineer to join the Localization team and own significant parts of our localization, mapping, and calibration stack as we scale autonomous ground operations across major airports. You'll take deep ownership of specific workstreams, contribute to the team's technical direction, and partner across the perception, planning, and platform interfaces to help drive the autonomous system from supervised operation to driverless. You'll work alongside the team's senior localization engineers. You Will • Take ownership of one or more core areas of the localization stack (LiDAR-inertial-GNSS state estimation, 3D mapping and map maintenance, or sensor calibration) and drive it to production reliability on real hardware at active airports • Contribute across the broader localization and mapping pipeline from sensor integration, performance tuning, regression testing, and deployment to new operating environments • Help design and build online validation that monitors localization integrity and cross-sensor consistency during live missions, detects drift, and integrates with the vehicle's safety architecture • Develop tooling for diagnostics, health logging, and post-mission analysis across the stack • Contribute to the regression, validation, and release-gating approach for localization changes deployed to active airports • Deploy, test, and iterate using data from real autonomous operations You Have • 8+ years in robotics or autonomous vehicles, with a track record of owning localization or state-estimation systems through production deployment on real hardware • Deep practical grounding in multi-sensor fusion and state estimation across LiDAR, IMU, GNSS, and cameras • Demonstrated technical leadership - driving architecture across teams, setting direction, and being the person others escalate to on hard estimation problems • Strong command of non-linear optimization (Ceres, GTSAM, g2o) and/or filtering (EKF, UKF), with the judgment to know when each applies • Strong modern C++ (C++17+) and deep working experience with Linux and ROS/ROS2 • Understanding of how calibration quality propagates through localization and perception, and how localization errors propagate into the safety case • BS or MS in Computer Science, Robotics, Electrical/Mechanical Engineering, or a related field We Prefer • MS or PhD with a focus on localization, state estimation, or calibration • Hands-on experience with multi-sensor calibration - intrinsic, extrinsic, and temporal • Experience with factor graphs, graph-based SLAM, or open-source tools like GLIM, LIO-SAM, Cartographer, Kalibr, Ceres, GTSAM • Experience building online/runtime monitoring and defining safety-relevant thresholds within a safety monitoring architecture • Track record of taking an autonomous system toward driverless operation

WHO WE ARE AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com http://www.aerovect.com. Working under the close guidance and supervision of the Head of Safety, the Senior SW Safety Engineer will execute core safety lifecycle tasks across AeroVect’s software and hardware platforms: • System Safety Analysis: Perform hazard identification and risk assessments (HARA, FMEA, FTA, STPA) on the autonomous software architecture and vehicle operation concepts. • Requirements Derivation: Derive, specify, and trace functional and technical safety requirements (FSRs / TSRs) for both supervised autonomy (safety driver present) and SDO unsupervised autonomy (driverless). • Cross-Functional Execution: Collaborate directly with systems, software, robotics, hardware, and test teams to ensure safety requirements are integrated, testable, and verified. • Safety Case Support: Assist in building safety case artifacts and verification evidence required for airport commercial deployment. YOU WILL • Conduct software hazard and safety analyses on perception, motion planning, localization, and vehicle control modules per ISO 26262-6 and SOTIF (ISO 21448). • Execute software FMEA/FTA, freedom-from-interference (FFI) analysis, and code-level hazard evaluations. • Derive Software Safety Requirements (SSRs) and define monitoring/fail-safe mechanisms within multi-core and Linux/RTOS software environments. • Review safety-critical C++/Python code and robotics middleware with development teams to ensure software safety standards are met. • Develop Safety Performance Indicators to measure safety performance over time. YOU HAVE • 5+ years of hands-on safety engineering experience in autonomous vehicles, automotive (ISO 26262), aerospace (DO-178C/DO-254), or industrial safety (IEC 61508). • Prior background working with autonomous driving systems or mobile robotics. • Proven ability to work under the technical mentorship of a Principal Safety Engineer in a high-velocity agile engineering team. • B.S. or M.S. in Computer Science, Electrical Engineering, Systems Engineering, Robotics, or a related discipline. • 5+ years of software development or SW safety experience in C++, Python, or ROS/ROS2 environments. • Deep understanding of software safety lifecycles, ASIL decomposition for software, unit/integration test strategies, and static analysis tools. • Hands-on experience analyzing autonomous vehicle software pipelines (perception, planning, fail-safe state machines).

WHO WE ARE AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com http://www.aerovect.com. You will own and extend the simulation tooling. A significant part of the role is test quality. A test suite that produces flaky failures does not provide usable information. Determinism, reproducibility, and verifying that each gate is capable of failing are ongoing responsibilities rather than one-off tasks. YOU WILL • Build and extend the capabilities of the simulation environment: integration with the production autonomy stack, the interfaces it consumes, vehicle and actor models, and the range of environmental and operational conditions that can be represented • Maintain and improve that integration as the autonomy stack evolves, including fidelity work where the difference between simulated and real inputs changes how the stack behaves • Build and operate scenario execution in the cloud: orchestration, parallelism, result aggregation, artifact capture, and runtime cost modelling • Build and extend the evaluation layer that turns a run into a verdict — assertions and pass/fail criteria precise enough to gate a release and stable enough to avoid false failures • Build failure-triage tooling: failure clustering, per-failure recordings, and dashboards that autonomy engineers can use without assistance • Extend the scenario authoring tooling used by the V&V team, across backend and frontend • Maintain simulation foundations: determinism and reproducibility, pipeline performance, and extending coverage to additional maps and sites YOU HAVE • Bachelor’s in Computer Science, Electrical Engineering, Robotics, or related field • Strong Python, with a track record of maintainable code in a shared codebase • Hands-on simulation experience for autonomous systems, familiarity with simulation platforms such as CARLA, Applied Intuition, Foretellix, NVIDIA Omniverse, IsaacSim, Gazebo, or a proprietary in-house simulator Working knowledge of simulation, modelling, and validation methodology, including how simulated results are used to support claims about real-world behaviour • Docker and Linux, distributed-systems fundamentals, and experience with GPU-based simulation environments CI/CD and cloud execution, experience integrating automated test workflows into CI for end-to-end validation coverage • Experience analyzing simulation output and telemetry to identify performance bottlenecks and failure modes • Debugging and profiling skills suited to distributed, GPU-bound systems WE PREFER • Master’s in Computer Science, Robotics, or related field • Experience designing and validating safety-critical systems in autonomous driving, aerospace, or robotics • Experience developing or maintaining autonomous vehicle software stacks (ROS/ROS2) • Cloud-based simulation infrastructure and large-scale distributed test execution • Sensor modelling (camera, lidar, radar), environment generation, or perception ground-truth pipelines • Automated testing, continuous integration, and data-driven validation • Log/bag re-simulation from recorded real-world data • Test-signal quality work: flake reduction, determinism debugging, golden-output comparison • Safety standards exposure: ISO 26262, ISO 21448 (SOTIF), UL4600, ISO 13849

WHO WE ARE AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com http://www.aerovect.com. As a Staff Software Engineer, Infrastructure (Cloud), you will own the data infrastructure and cloud systems that power AeroVect's autonomous driving platform. You'll design and scale the pipelines that move operational data from real-world deployments into the systems that drive development, testing, and continuous improvement — ensuring reliability and performance This is a highly impactful role at the intersection of cloud infrastructure and data engineering. You'll have real ownership — designing systems from the ground up, not inheriting a finished stack. The opportunity to grow into a technical leadership role is real as the team scales. You Will • Design, build, and maintain scalable data pipelines that move operational data from on-prem systems into cloud infrastructure • Architect and manage cloud-based infrastructure (AWS) for scalable computation, data processing, and system telemetry • Integrate on-prem and cloud data flows into a cohesive, reliable data architecture • Build and maintain CI/CD pipelines to enable rapid, reliable software delivery and validation across simulation and real-world testing environments • Implement and manage infrastructure-as-code (Terraform, CloudFormation) for consistent, automated provisioning • Develop internal services and automation tools to streamline data ingestion, processing, and observability • Establish and enforce best practices for data reliability, pipeline observability, and system security • Drive root-cause analysis for data infrastructure and pipeline issues; design long-term solutions to improve system resilience • Collaborate with autonomy and systems engineers to define scalable data interfaces and cloud deployment strategies You Have • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field • 7+ years of experience building cloud infrastructure and data systems for large-scale distributed systems • Strong proficiency in Python with a focus on data pipeline development and automation • Hands-on experience with Kafka, Kubernetes, and gRPC for building scalable, high-throughput data systems • Deep expertise with AWS cloud services including compute, storage, and data processing • Experience with CI/CD platforms (Jenkins, GitHub Actions, CircleCI) • Proficiency with containerization and orchestration (Docker, Kubernetes) • Experience automating deployments with Terraform or CloudFormation • Familiarity with Git-based workflows, code review processes, and collaborative software development We Prefer • Experience integrating on-prem and cloud data flows in a hybrid infrastructure environment • Background in data engineering for robotics, autonomous systems, or real-time operational data • Knowledge of monitoring, logging, and alerting tools such as Prometheus, Grafana, or the ELK Stack • Familiarity with networking, security, and distributed system performance optimization • Experience supporting safety-critical, real-time, or high-availability systems

WHO WE ARE AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com http://www.aerovect.com. We are looking for a Senior Software Engineer to join the Localization team and take ownership of our calibration systems — from robustifying and stabilizing the existing offline calibration stack, through adapting it for new sensors and environments, to building online calibration validation for continuous autonomous operations at major airports. Beyond calibration, you will contribute to the broader localization, mapping, and sensor integration efforts as the team scales. You will work under the supervision of a Staff Localization Engineer and collaborate closely with the Perception, Planning, and Infrastructure teams. You Will • Own the calibration stack end-to-end — improve reliability of existing offline calibrations, close coverage gaps across the sensor suite (LiDAR, IMU, GNSS, cameras, radar), and ensure every calibration is repeatable, traceable, and has clear pass/fail criteria • Design and build an online calibration validation system that monitors cross-sensor consistency during live missions, detects drift, and integrates with the vehicle's safety architecture • Contribute to the localization and mapping pipeline — sensor integration, performance tuning, regression testing, and deployment to new operating environments • Develop tooling for calibration health logging, diagnostics, and post-mission analysis • Deploy, test, and iterate using data from real autonomous operations at active airports You Have • 5+ years of experience in robotics or autonomous vehicles with hands-on work in sensor calibration, localization, or state estimation • Strong practical knowledge of multi-sensor calibration - intrinsic, extrinsic, and temporal - across LiDARs, IMUs, GNSS, and cameras • Proven experience with non-linear optimization frameworks (Ceres, GTSAM, g2o) or filtering approaches (EKF, UKF) • Strong C++ skills (C++17+) and working experience with Linux and ROS/ROS2 • Understanding of how calibration quality propagates through localization and perception • BS or MS in Computer Science, Robotics,Electrical/Mechanical Engineering, or related field We Prefer • MS or PhD with a focus on calibration, localization, or state estimation • Experience building online/runtime calibration monitoring for deployed autonomous systems • Experience with factor graphs, graph-based SLAM, or open-source tools like Kalibr, LIO-SAM, GLIM, Ceres, GTSAM • Track record of deploying calibration or localization systems on real hardware in production environments • Experience defining safety-relevant thresholds and working with safety monitoring architectures • Familiarity with OpenCV, PCL, or Open3D