“If you are excited about applying to LLMs to tackle real-world challenges in government procurement, this is a perfect opportunity for you. Be a part of the team of research and machine learning scientists building deployable real-world ML applications from ground up and get mentored by some of the best minds in AI during the process.”
- Maithrreye Srinivasan, Machine Learning Scientist and Amor Provins, Product Owner, Advanced Technology
This is a paid Residency that will be undertaken over a twelve-month period with the potential to be hired by our client, Publicus, 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.
Publicus is Canada’s fastest growing govtech company, building the data and intelligence layer for government procurement: helping businesses find and win public-sector contracts and helping governments cut waste, prevent fraud, and buy Canadian. We millions of fragmented, multimodal procurement records into searchable, trusted intelligence.
We are AI-native by default: AI is part of everything we build, product and operations alike, which lets a small team move at a pace a far larger one cannot.
A central objective of this initiative is to transform how governments and businesses interact with procurement documents by reducing manual review, accelerating information retrieval, and improving data quality. Through intelligent automation, Publicus aims to lower procurement processing costs, improve operational efficiency, and provide trusted procurement intelligence that supports faster, more informed public sector decision-making.
In collaboration with Amii, Publicus is developing next-generation AI capabilities for government procurement document intelligence through the generation of realistic synthetic multimodal procurement documents, including adversarial variants that closely resemble authentic procurement documents while containing safe, non-sensitive data. These datasets will be used to train, evaluate, and benchmark multimodal AI models, enabling robust information extraction and reliable deployment within secure government environments.
This project develops advanced AI capabilities for government procurement document intelligence using Document AI, computer vision, optical character recognition (OCR), Vision Language Models (VLMs), and Large Language Models (LLMs). The goal is not a research artifact but a robust, deployable multimodal pipeline that understands, extracts, validates, and benchmarks key information from complex government documents — RFPs, contracts, invoices, and supporting procurement records — and runs reliably in secure, low-compute government environments.
A core component of the project is developing realistic synthetic multimodal procurement documents to overcome the limitations of publicly available procurement datasets, which are often incomplete or heavily redacted. The Resident will generate synthetic and adversarial document variants, investigate state-of-the-art document understanding models, benchmark and fine-tune multimodal AI systems, and develop reliable extraction pipelines that improve robustness, efficiency, and deployment readiness for secure, low-compute environments.
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, large language models, along with proven experience in applied settings.
- Design, evaluate, and ship multimodal document intelligence pipelines using OCR, computer vision, Vision Language Models (VLMs), and Large Language Models (LLMs) for government procurement document understanding — orchestrating models and agentic workflows through to production, not stopping at notebook prototypes.
- Prepare, curate, and annotate procurement datasets, including realistic synthetic and adversarial document variants, for model training, fine-tuning, benchmarking, and evaluation.
- Conduct applied research in Document AI, computer vision, multimodal learning, and information extraction — and translate it into robust, deployable extraction pipelines that run reliably in secure, low-compute government environments.
- Benchmark and evaluate state-of-the-art OCR engines, Document AI models, and Vision Language Models, while investigating efficient inference techniques such as quantization, model compression, and optimized transformer serving.
- Ship client-focused MVPs fast and iterate with evidence — tests, benchmarks, logs, and clear verification steps. At Publicus, if it isn't verifiable, it isn't done.
- Engage in regular client meetings, contributing to presentations and reports on project progress.
- A graduate degree (MSc or PhD) in Computer Science or a related field with specialization in Computer Vision, Document AI, multimodal learning, or OCR — or equivalent demonstrated experience shipping applied ML systems. We weigh what you have built and can prove works as heavily as credentials.
- Research or project experience in Document AI, computer vision, OCR, or Vision Language Models (VLMs).
- Proficiency in Python and modern AI frameworks such as PyTorch, Hugging Face Transformers, vLLM, Unsloth, OpenCV, TensorFlow, and related machine learning libraries.
- Familiarity with linux, Git version control, and writing clean code.
- A positive attitude towards learning and understanding a new applied domain.
- Must be legally eligible to work in Canada.
- Experience with synthetic data generation and multimodal foundation models (VLMs/LLMs).
- Experience with building, training, evaluating, and quantizing machine learning models to achieve optimized performance in production environments, with a focus on low-latency, resource-efficient edge-device deployment.
- Knowledge of MKL, cuDNN, and acceleration techniques for math computing is a plus.
- Experience with deploying machine learning models in production environments or strong software engineering (or MLE) skills is a plus.
- Publication record in peer-reviewed academic conferences or relevant journals in ML or Applied AI (especially in computer vision).
- 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
Besides gaining industry experience, additional perks include:
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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)
One of Canada’s three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world’s top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.
If this sounds like the opportunity you've been waiting for, please don’t wait for the closing July 28, 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. 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.
Please visit https://www.amii.ca/ for more information
