Machine Learning Engineering Intern developing innovative AI solutions for contact centers at Cresta. Collaborating with top researchers and engineers in AI to unlock customer experience potential.
A(
Machine Learning Resident – Client: Enriched Ag
Posted 4 months ago
About the role
- 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)
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Report this job
Found something wrong with the page? Please let us know by submitting a report below.
MLOps/LLMOps Architect designing AI solutions for a next - gen AI platform in Canada. Collaborating with teams on architecture, deployment, and governance in AI environments.
Staff MLOps Engineer responsible for building infrastructure for AI/ML at NBCUniversal. Managing large media datasets, deploying models, and automating data pipelines.
Deep Learning Engineer at NBCUniversal implementing algorithms in computer vision and graphics. Transforming high dimensional data into high - fidelity content using advanced techniques.
Staff Deep Learning Engineer at NBCUniversal implementing core algorithms for 2D and 3D media datasets. Collaborating with cofounders and deploying large - scale algorithms for high - fidelity content.
Senior Machine Learning Engineer at DraftKings shaping player experiences through machine learning solutions. Leading initiatives to improve engagement and retention via advanced data strategies.
Machine Learning Developer at Rocket Innovation Studio designing frameworks for automated decision - making. Collaborating with data scientists to develop algorithms and hosting trained models into business processes.
MLOps Developer leading major workstreams for AI - enhanced aerial surveillance platforms. Focused on deploying deep learning models and influencing MLOps strategy.
ML Engineer on the Alerts Team developing AI for crisis intelligence. Building and maintaining ML models in a dynamic environment.
Senior Staff Machine Learning Engineer at Workiva defining enterprise - level AI architecture and solutions. Leading technical direction and influencing secure AI platform design across multiple teams.