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BHF Robotics

Robotics Software Developer – ROS2, State Estimation, Perception

Markham, ON, Canada

Full-time

Apply About employer

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Job details

Job type: Full-time
Apply by: Dec 8, 2026
Experience: Experience: 1+ years of professional/research engineering experience in robotics and/or autonomous vehicles.
Posting language: English
Posted: Nov 8, 2026

Original job description

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 skilled Robotics Software Developers with experience in ROS2, State Estimation, and Perceptions to join our robotics development team. The ideal candidate will have hands-on experience in real-time robotic operations and perceptions, along with the ability to design and integrate complex robotic software systems from concept to deployment. 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, as well as develop generalized perception models.

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).
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.
System integrations for autonomy software stacks - integrating planning, perception, and control modules into scalable and maintainable frameworks.
Produce computationally efficient software that can meet real-time requirements
Balance hands-on development, code reviews, and research to achieve product-driven milestones in a fast-paced startup environment.
Debug complex interactions between hardware and software in real-world conditions.
Hands-on experience training deep learning models for detection and segmentation.
Participate in on-machine testing, including occasional travel to the field to experience the product in its intended use.

Qualifications

Required Skills & Experience:

Education: Master’s, Ph.D. in Robotics, Mechatronics, Mechanical Engineering, Electrical Engineering, or a related discipline.
Experience: 1+ years of professional/research engineering experience in robotics and/or autonomous vehicles.
Development Skills: Exceptional C++ / Python programming skills with a strong grasp of modern software engineering practices (Git, CI/CD, unit testing, profiling).
Middleware & Environment: Hands-on experience with ROS2 and deploying containerized applications using Docker in Linux environments. Familiarity with ROS2 for integrating planners, controllers, and perception modules.
Classical Estimation Theory: 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: Familiar with integrating, calibrating, synchronizing, and fusing data from sensors such as cameras, LiDAR, radar, GNSS, wheel encoders, and/or IMUs in real-world robotic systems.

Preferred Skills & Experience:

Familiarity with visual-inertial (VIO) or lidar-inertial (LIO) odometry frameworks.
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).
Model optimization and deployment on embedded GPUs (ONNX, TensorRT, quantization).
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.

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.

You must include a cover letter to be considered for this position.

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.

Apply About employer

More about this job

Responsibilities

Develop and optimize real-time state-estimation, sensor-fusion, and perception software for autonomous agricultural robots, integrating autonomy modules and deploying efficient C++ applications on edge hardware. Validate systems through HIL simulation and field testing, troubleshoot hardware-software interactions, and contribute to code reviews and product-focused development.

Requirements

A master's or Ph.D. in robotics, mechatronics, mechanical engineering, electrical engineering, or a related discipline is required, along with at least one year of robotics or autonomous-vehicle engineering experience. Candidates need strong C++ and Python skills, hands-on ROS2 and Docker experience in Linux, knowledge of estimation methods and sensor integration, and willingness to work on-site and in the field.

Skills

C++
Python
ROS2
State Estimation
Sensor Fusion
Real-Time Systems
Computer Vision
Deep Learning
Docker
Linux
GNSS/RTK
LiDAR
IMU Integration
Visual-Inertial Odometry
Lidar-Inertial Odometry
Embedded GPU Deployment

Benefits

Extended Health Care
Dental Care
Vision Care
Employee and Family Benefits Program
Stock Options
Bonus Plan
Global Travel Assistance
Flexible Work Schedule
Company-Covered Gym Access

Visa sponsorship

Not detected in the job text

Keywords

ROS2
C++
Python
State Estimation
Sensor Fusion
Extended Kalman Filter
Unscented Kalman Filter
Factor Graphs
Particle Filters
Graph-Based SLAM
Visual-Inertial Odometry
Lidar-Inertial Odometry
GNSS/RTK
LiDAR
IMU
Wheel Odometry
Radar
Computer Vision
Deep Learning
Detection and Segmentation
Docker
Linux
Git
CI/CD
Unit Testing
Profiling
ONNX
TensorRT
Quantization
Gazebo

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