Machine Learning Engineer

Herd-i Operations Limited

Company overview

Herd-i Locomotion is a non-intrusive, camera-based locomotion scoring system for dairy cows, developed by Herd-i (https://www.herd-i.com). We build products for dairy farmers using cutting-edge artificial intelligence.

Job purpose

We are seeking a talented and experienced Machine Learning Engineer to join our team and help build an AI product aimed at improving dairy herd health and performance. The successful candidate will enhance our existing models and improve our MLOps pipeline.

Role details

Position: Full-time

Location: Christchurch office

Reports to: Lead Machine Learning Engineer

Liaises with: Herd-i CTO, Herd-i software developers, Herd-i staff, and clients

Responsibilities and deliverables

Develop, optimise, and maintain machine learning models, including cow detection models, keypoint detection models, and regression models.

Design and implement MLOps pipelines to streamline model training, deployment, and monitoring.

Conduct data preprocessing, feature engineering, and model evaluation to ensure high-performance outcomes.

Improve the accuracy of cow identification and detection models, with a focus on early illness detection.

Collaborate with cross-functional teams to understand business needs and implement AI solutions that meet them.

Stay current with advances in machine learning and AI, and apply them to our products.

Support other developers, including performing code reviews.

Contribute to continuous process improvement.

Qualifications and experience

You must have:

A bachelor's degree or above (ideally a PhD or master's) in Computer Science, Data Science, Machine Learning, or a related field.

1-2 years' experience developing and deploying machine learning models in a production environment.

Strong proficiency in Python and experience with relevant libraries and frameworks, such as PyTorch or TensorFlow.

Expertise in computer vision, including object detection models (such as RT-DETR or YOLO) and keypoint detection models.

Experience with regression models, such as XGBoost, for scoring and prediction.

Familiarity with MLOps practices, including CI/CD pipelines, containerisation, and cloud services.

Strong problem-solving skills, and the ability to work both independently and collaboratively.

Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

It would also be an advantage if you had:

Experience in the agricultural or dairy industry, particularly in improving herd health and performance.

Knowledge of data visualisation tools and techniques.

Experience with large-scale data processing and management.

What we offer

Competitive salary and benefits package.

The opportunity to work on cutting-edge AI technologies and their application in agriculture.

A collaborative and innovative work environment.

Career growth and development opportunities.