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BHF Robotics

Perception Engineer

Markham, ON, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: May 8, 2027
Experience: At least 2+ years of experience as a Computer Vision, deep learning, machine learning engineer/researcher.
Posting language: English
Posted: Nov 9, 2026

Original job description

About the Company: BH Frontier Solutions Inc. is a venture-backed fast-growing agricultural technology 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, and help growers to build a fully autonomous, efficient and sustainable farming system. We would like to 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.

About the Role: The ideal candidate has a solid background in perceptions. Creative problem solvers, quick learners and comfortable devising and experimenting with novel approaches. Highly productive and enjoys dealing with ambiguity and applying new methodologies. Have a strong attention to detail, data accuracy and quality of output. Self-motivated and possess entrepreneurship, passion and curiosity for understanding and interrogating complex data. Hold a demonstrated ability to work independently, with a disciplined approach and a strong sense of responsibility. Management ability is an asset, demonstrating the potential to excel in technical leadership roles.

Responsibilities:

Collaborate with the team and other stakeholders to evaluate state-of-the-art computer vision techniques and applications in plant detection, tracking and classifications in various agricultural settings, particularly with deep-learning and machine-learning approaches.
Synthetic data generation and pipeline management.
Devise, implement and interpret deep learning and machine learning algorithms to address selected research questions in perceptions and precision agriculture.
Help shape the direction of deep learning and artificial intelligence within BHF.
Design computer vision algorithms for a broad range of applications relating to agriculture (real time object detection, object tracking etc.).
Develop, apply and optimize computer vision models for large-scale and real world applications, ensuring models are efficiently integrated and perform optimally in production.
Design and conduct tests to validate computer vision models based on agreed metrics.
Take ownership of the computer vision project from start to finish, which includes building data pipelines, designing, deploying & maintaining production quality CV models in collaboration with other teams.
Benchmark and refine computer vision and machine learning algorithms, including enhancing data pre-processing and augmentation for better accuracy and efficiency.
Collaborate with cross-functional teams to define vision system requirements and capabilities.
Familiarity with foundational model

Qualifications:

MSc/PhD degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, or a related field.
At least 2+ years of experience as a Computer Vision, deep learning, machine learning engineer/researcher.
In-depth knowledge and experience in computer vision projects, with a strong emphasis on real-world applications.
Proven track of record in top academic conferences/publications.
Experience with successfully completing computer vision projects from scratch to deployment at production level.
Hands-on experience with ROS/ROS2 in robotic perception and autonomous systems development.
Proven expertise in designing and implementing vision systems for robotic applications.
Solid understanding of foundational statistics concepts and ML algorithms: linear/logistic regression, Random Forest, boosting, XGBM, k-NN, Naive Bayes, Decision Trees, SVM, etc.
Good theoretical as well as practical knowledge of deep learning architectures such as LSTM, RNN and CNN and Transformer based models.
Algorithm and model development experience for large-scale applications.
Experience running accuracy experiments and systematically improving performance.
Familiarity with scientific computing libraries such as numpy, pandas, scikit and image processing libraries such as OpenCV and scikit-image.
Solid understanding and practical experience of containerizing Deep Learning models for deployment purposes in a scalable manner.
Experience with SQL and NoSQL databases and ETL tools.
Willing to perform tasks on farms from time to time.
Strong cross-team communication and collaboration skills. Comfortable being part of a small team of engineers working in an energetic fast paced start-up environment and effective as part of a distributed team.
Proficiency in C++, Python, or other relevant programming languages, with solid skills in object-oriented software development.
Experience in fine-tuning diffusion models (LoRA, ControlNet, inpainting) is a plus.
Experience leading engineering teams is a plus.

Pay range and compensation package: Highly competitive compensations, growth opportunities, and the chance to make a tangible impact in AgTech.

Equal Opportunity Statement: Please include your resume, summary of your previous project, and cover letter in the application.

Benefits:

Extended Health & Dental & Vision Care Plans
Employee & Family Benefits Program
Global Travel Assist Plan
Paid Extra Vacation / Super Weekends Plan
Unparalleled Stock Options Grant + Bonus Plan

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.

Apply About employer

More about this job

Responsibilities

Develop, test, optimize, and deploy computer vision and machine learning models for agricultural robotics, including plant detection, tracking, and classification. Own projects from data pipeline development through production deployment, while collaborating with stakeholders and cross-functional teams to shape perception capabilities.

Requirements

Requires an MSc or PhD in computer science, engineering, robotics, or a related field, plus at least two years of computer vision, deep learning, or machine learning experience. Candidates should have production deployment and robotic perception experience, strong programming and ML skills, and the ability to collaborate effectively in a fast-paced startup environment.

Skills

Computer Vision
Deep Learning
Machine Learning
Robotic Perception
ROS/ROS2
Object Detection
Object Tracking
Synthetic Data Generation
Model Deployment
Python
C++
OpenCV
Data Pipelines
SQL and NoSQL Databases
Statistical Modeling
Cross-Functional Collaboration

Benefits

Extended Health Care
Dental Care
Vision Care
Employee and Family Benefits Program
Global Travel Assistance
Paid Extra Vacation
Stock Options
Bonus Plan

Visa sponsorship

Not detected in the job text

Keywords

Agricultural Robotics
Precision Agriculture
Computer Vision
Deep Learning
Machine Learning
Artificial Intelligence
Robotic Perception
ROS
ROS2
Object Detection
Object Tracking
Plant Classification
Synthetic Data Generation
Data Pipelines
Model Deployment
Production Systems
CNN
RNN
LSTM
Transformers
Diffusion Models
LoRA
ControlNet
Inpainting
Python
C++
NumPy
Pandas
Scikit-Learn
OpenCV

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