Machine Learning Resident - Client: Enriched Ag (1 year term)

“If you are interested in the application of vision AI for modern smart agriculture technology, this is the right opportunity for you. Be a part of the team of research and machine learning scientists building a revolutionary AI system from the ground up and get mentored by some of the best minds in AI during the process.”

 - Xu Han, Machine Learning Scientist, Advanced Technology 

Description

About the Role

This is a paid residency that will be undertaken over a 12-month period with the potential to be hired by our client, Enriched Ag, afterwards (note: at the discretion of the client). The Resident will report to an Amii Scientist and regularly consult with the client team to share insights and engage in knowledge transfer activities. Successful candidates will be members of a cross-functional project team with backgrounds in ML research, project management, software engineering, and new product development. This is a rare opportunity to be mentored by world-class scientists and to develop something truly  impactful.

About the Client

Enriched Ag Canada Inc. (“Enriched Ag”) is a Calgary-based agricultural technology company that develops data-driven intelligence solutions for ranching and cropping operations by integrating domain expertise, vehicle-based imaging systems, and machine learning. Founded in 2021, the company’s mandate is to advance data-driven agriculture by delivering high-resolution field data, integrated satellite and modelling insights, and applied agronomic intelligence to enable producers to improve productivity, sustainability, and the long-term health of agricultural working lands.

About the Project

The project focuses on advancing applied computer vision and multimodal AI for large-scale rangeland, pasture, and cropland monitoring. Enriched Ag has built one of the most extensive vehicle-based visual datasets focused on rangeland and pasture systems and currently has over a dozen custom machine learning models deployed in commercial use, with several additional models in active development. A core objective of this residency is to further develop and operate this model stack within a Canadian-controlled machine learning infrastructure, ensuring that data, pipelines, ground-truth generation and validation, model training, evaluation, and deployment are managed and scaled in Canada. The residency will center on strengthening and extending this model ecosystem by improving the reliability and generalization of existing vision models while exploring new approaches to representation learning and multimodal reasoning in complex, real-world agricultural environments. In addition to core vision research, the project will translate model outputs into interpretable, decision-ready insights, with opportunities to incorporate vision-language and large language models as an interface between field-scale data and end users.

Required Skills / Expertise

Are you passionate about building great solutions?  You’ll be presented with opportunities to both personally and professionally develop as you build your career. We’re looking for a talented and enthusiastic individual with a solid background in machine learning, specifically in multimodal AI and computer vision. 

Key Responsibilities:

• Design, implement, optimize, and evaluate models for a full stack of core vision tasks and multimodal development, including object detection, image segmentation, image search, text-image retrieval, image understanding, advanced vision-language tasks, etc.


• Prepare, curate, and preprocess high-quality datasets for training or fine-tuning, and validating models.


• Utilize state-of-the-art ML frameworks, tools and open-source libraries to enhance model performance, accelerate workflows, and optimize data processing.  


• Undertake applied research on traditional ML, modern large vision model, and vision language model (VLM) techniques to address the limitations in existing models.


• Optimize ML pipelines to ensure efficiency, scalability, and real-time processing capabilities.


• Collaborate with the project team and stakeholders to develop MVP and client focused solutions.


• Engage in regular client meetings, contributing to presentations and reports on project progress.

Required Qualifications: 

• Completion of a Computer Science (or a related graduate degree program) MSc. or PhD with specialization in vision AI and vision-language multimodal modeling.


• Proficient in developing and training, fine-tuning and evaluating machine learning and deep neural network models in PyTorch and/or TensorFlow.


• Solid experience with modern ViT and CNN models for real world visual recognition tasks (e.g. object detection, instance segmentation) and other related vision tasks (e.g. image retrieval, image captioning).


• Hands-on experience with foundational vision language models (e.g. CLIP, LLaVA).


• Proficient in Python programming language and related ML frameworks, libraries, and toolkits (e.g., Scikit-learn, TensorFlow, PyTorch, OpenCV, Pandas, HuggingFace).


• Familiarity with Linux, Git version control, and writing clean code.


• Comfortable with quick prototyping in a business environment.


• A positive attitude towards learning and understanding a new applied domain .


• Must be legally eligible to work in Canada.

Preferred Qualifications:

• Familiarity with and hands-on experience with 3D vision problems (e.g. 3D reconstruction), Vision-Language Reasoning (VLR), diffusion models, and LLM models.


• Extensive real-world experience, including building production-level AI, handling non-standard vision tasks and edge cases.


• Publication record in peer-reviewed academic conferences or relevant journals in machine learning.


• Experience/familiarity with software engineering best practices.


• Experience with deploying machine learning models in production environments or strong software engineering (or MLE) skills is a plus.

Non-Technical Requirements: 

• Desire to take ownership of a problem and demonstrated leadership skills.


• Interdisciplinary team player enthusiastic about working together to achieve excellence.


• Capable of critical and independent thought.


• Able to communicate technical concepts clearly and advise on the application of machine intelligence.


• Intellectual curiosity and the desire to learn new things, techniques, and technologies.

Why You Should Apply

Besides gaining industry experience, additional perks include:

• Work under the mentorship of an Amii Scientist for the duration of the project


• Participate in professional development activities


• Gain access to the Amii community and events


• Get paid for your work (a fair and equitable rate of pay will be negotiated at the time of offer)


• Build your professional network


• The opportunity for an ongoing machine learning role at the client’s organization at the end of the term (at the client’s discretion)

How to Apply

If this sounds like the opportunity you've been waiting for, please don’t wait for the closing date of February 27, 2026  to apply. We’re excited to add a new member to the Amii team for this role, and the posting may come down sooner than the closing date if we find the right candidate before the posting closes! When sending your application, please send your resume and cover letter indicating why you think you'd be a fit for Amii and the role. In your cover letter, please include one professional accomplishment you are most proud of and why.

Applicants must be legally eligible to work in Canada at the time of application.

Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity, religion, gender identity, sexual orientation, age or disability. Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and won’t be used in the selection process.