Robotics Software Developer – Localization, State Estimation, & Sensor Fusion

About the Company: BHF Robotics is a venture-backed, fast-growing agricultural robotics company that is currently transforming the technological landscape in agriculture. We specialize in designing and manufacturing agricultural robots that leverage frontier technology and AI research to tackle significant issues in agriculture. We apply artificial intelligence, perception, electrification technology, and robotics that enable data-driven agricultural management and precision treatment, helping growers to build a fully autonomous, efficient, and sustainable farming system. We invite the smartest and most committed engineers, scientists, agricultural experts, and technologists, who united around the mission to drive the next Agtech revolution, to join us. Job Summary We are seeking a highly skilled Robotics Software Developer with expertise in State Estimation, Localization, and Sensor Fusion to join our autonomy team. In this role, you will help develop and implement state-of-the-art algorithms that allow our agricultural robots to precisely self-localize and estimate their state in highly challenging, unstructured, and dynamic farming environments. Agricultural fields present severe localization hurdles, including extreme wheel slip, uneven terrain, dust, and GPS-denied zones under crop canopies. To solve these, you will bridge the gap between classical estimation theory (EKF, UKF, factor graphs) and modern learning-based spatial AI approaches. The ideal candidate will design, train, and deploy robust real-time estimation frameworks from theoretical concept to field-deployed, production-grade software. Key Responsibilities State Estimation & Sensor Fusion: Design, implement, and optimize robust, real-time state estimation and multi-sensor fusion pipelines (fusing IMUs, GNSS/RTK, LiDAR, cameras, and wheel odometry). Robust Off-Road Localization: Build and refine advanced SLAM (visual/lidar-inertial) and filtering frameworks optimized to maintain decimeter-level localization accuracy despite high-vibration and unstructured agricultural terrains. System Modelling & Identification: Perform system identification and build high-fidelity kinematic, dynamic, and learned models of our robotic platforms. Production C++ Development: Write clean, deterministic, and computationally efficient C++ code capable of running within strict real-time CPU/GPU budgets on edge hardware. Testing & Validation: Conduct hardware-in-the-loop (HIL) simulations and on-machine field testing to validate localization accuracy, gather dataset training logs, and verify system stability. Collaboration & Research: Stay at the forefront of academic and industry research in spatial AI, state estimation, and learning-based localization, turning state-of-the-art papers into working code. Qualifications Required Skills & Experience: Education: Master’s and Ph.D. in Robotics, Mechatronics, Mechanical Engineering, Electrical Engineering, or a related discipline Experience: 2+ years of professional/research engineering experience in robotics and/or autonomous vehicles. Development Skills: Exceptional C++ and Python programming skills with a strong grasp of modern software engineering practices (Git, CI/CD, unit testing, profiling). Classical Estimation Theory: Deep theoretical understanding of and hands-on experience with state-estimation methods and stochastic systems. (including EKFs, UKFs, factor graphs, particle filters, and graph-based SLAM.) Sensor Integration: Proven experience integrating, calibrating, synchronizing, and fusing data from sensors such as cameras, LiDAR, radar, GNSS, wheel encoders, and/or IMUs in real-world robotic systems. Learning-Based Robotics: Proven experience applying machine learning or deep learning to spatial estimation challenges (using frameworks like PyTorch or TensorFlow, and optimization/deployment tools like TensorRT or ONNX). Math Foundations: Solid understanding of linear algebra, rigid body dynamics, and numerical optimization. Middleware & Environment: Hands-on experience with ROS2 and deploying containerized applications using Docker in Linux environments. Preferred Skills & Experience: Familiarity with visual-inertial (VIO) or lidar-inertial (LIO) odometry frameworks. Experience with factor graph optimization libraries (e.g., GTSAM, Ceres Solver, g2o, or RTAB-Map). Experience handling state estimation challenges unique to off-road or agricultural environments (e.g., mud, high wheel slip, high dust, dynamic crop canopies, GPS-denied environments). Exposure to physics simulators (Gazebo, Isaac Sim) for closed-loop localization testing. Working knowledge of computer vision frameworks (OpenCV, ROS perception stack, or deep learning-based methods). Hands-on experience with system architecting for robotic or autonomous systems.Strong understanding of embedded systems and real-time computing. Hands-on experience with motion capture systems (e.g., OptiTrack, Vicon, Qualisys) in robotics applications. Soft Skills: Excellent analytical, problem-solving, and system-level thinking. Highly self-motivated and comfortable working in a fast-paced startup environment with startup-oriented hours. Commitment to working onsite five days a week to contribute to a collaborative in-office culture. Willingness to work hands-on in the field alongside the hardware and agronomy teams during testing and validation. Pay range and compensation package: Competitive compensations, growth opportunities, and the chance to make a tangible impact in AgTech. Equal Opportunity Statement: Please include your resume and cover letter in the application. Applications without cover letter will not be reviewed. Benefits: Extended Health & Dental & Vision Care Plans Employee & Family Benefits Program Unparalleled Stock Options Grant + Bonus Plan Global Travel Assist Plan Flexible Work Schedule / Super Weekends Plan Company covered Gym Access Why Join Us: You will lead the field service team for deployment of next-generation autonomous agricultural robotic systems that transform the industry. This role offers extensive exposure to technical management and leadership. You will lead the design and deployment of next-generation physical AI systems that transform the industry. This role offers extensive exposure to technical management and leadership, AI system design, and the full product lifecycle — providing hands-on experience in end-to-end development, from concept to deployment. Real opportunities of becoming Tech Lead → Head of Engineering → CTO in short period. Collaborate with leading experts in AI, robotics, and autonomous system. Competitive compensation, growth opportunities, and the chance to make a tangible impact in Physical AI and AgTech.

Design and implement real-time state estimation and multi-sensor fusion pipelines for agricultural robots in unstructured environments. Develop production-grade C++ code and conduct field testing to validate localization accuracy and system stability.

Requires a Master's or PhD in Robotics or a related engineering field with 2+ years of professional experience. Must possess strong C++ and Python skills and deep theoretical knowledge of stochastic systems and sensor integration.

• Extended Health & Dental & Vision Care Plans • Employee & Family Benefits Program • Stock Options Grant • Bonus Plan • Global Travel Assist Plan • Flexible Work Schedule / Super Weekends Plan • Company covered Gym Access

• DockerSouhaitée
• C++Souhaitée
• PythonSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• C++
• Python
• State Estimation
• Sensor Fusion
• SLAM
• ROS2
• Docker
• PyTorch
• TensorFlow
• Linear Algebra
• Rigid Body Dynamics
• Numerical Optimization
• EKF
• UKF
• Factor Graphs
• Lidar-Inertial Odometry

• Engineering
• Software
• Agriculture
• Technology
• Manufacturing

Formation minimale

Maîtrise

Expérience minimale

2+ ans

Postuler avant le

28 févr. 2027

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Niveau d’expérience

Entry level

Mode de candidature

La candidature directe est offerte