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 Tensor Flow, 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…