Machine Learning Resident at Enriched Ag focusing on vision AI for agriculture technology. Engaging in hands-on research and development with mentoring in a fast-paced environment.
Responsibilities
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
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
Engage in regular client meetings, contributing to presentations and reports on project progress
Requirements
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
Benefits
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)
Machine Learning Resident for Theragraph involved in developing solutions for health datasets. Collaborating in a cross - functional team under the mentorship of an Amii Scientist.
Senior ML Engineer leading the scaling and innovation of machine learning initiatives at Wisedocs. Collaborating with other engineers to integrate the ML system into the platform for insurance tech.
Lead ML Engineer developing scalable data pipelines and ML systems for Newfold Digital. Collaborate with cross - functional teams using Python, SQL, and cloud ML platforms in an applied ML environment.
Senior Machine Learning Engineer designing and optimizing ML/AI systems for digital forensic tools. Collaborating with cross - functional teams to lead initiatives and drive innovation in digital investigations.
Senior MLOps Engineer focusing on applied MLOps for CreatorIQ, bridging data science and production - grade efficiency. Responsible for annotation workflows and cost - efficient model evaluation.
Senior AI/ML Engineer leading design and deployment of high - impact AI solutions at CloudWerx. Bridging predictive modeling with next - generation Agentic AI to solve client challenges.
Machine Learning Resident developing AI - assisted tools for geotechnical site characterization. Involves collaboration with scientists and engineers to develop predictive ML models.
Machine Learning Resident at Hines Health Services focusing on AI - driven medical workforce solutions. Supporting the development of scalable, AI - powered recruitment platforms over a 6 - month residency.
Software Engineer, Machine Learning developing next - generation AI technologies for clinical trial platforms. Building scalable data pipelines, optimizing model performance, and collaborating with cross - functional teams in a hybrid setting.
Senior Machine Learning Engineer at BenchSci focusing on developing machine learning models for biomedical applications. Collaborating with a team to enhance scientific experiments through AI - driven solutions.