- Plan, design, and oversee AI/ML projects from concept to deployment.
- Define milestones, monitor progress, and ensure timely delivery.
- Build, train, evaluate, and optimize machine learning models across natural language processing, computer vision, and multimodal domains, including LLMs, VLMs, and vision-specific models (e.g., CNNs, ViTs, diffusion-based models).
- Apply a range of techniques such as transfer learning, parameter-efficient fine-tuning, prompt engineering, knowledge distillation, multimodal fusion, and efficient inference methods (quantization, pruning, model compression).
- Work with recent large language models and reasoning-oriented models, applying techniques such as supervised fine-tuning, structured prompting, retrieval-augmented generation (RAG).
- Read and experiment with recent technologies and research papers; evaluate applicability to projects.
- Apply strong foundations in data structures, algorithms, object-oriented programming, and software design patterns to build reliable AI systems.
- Write clean, maintainable, and well-documented code following established team standards. Practice unit/integration testing, CI/CD pipelines, and version control (Git/GitHub).
- Leverage containerization and orchestration tools such as Docker and Kubernetes for reproducible development and deployment.
- Design and consume APIs (REST/GraphQL) for integrating AI models into larger systems.
- Guide junior engineers through technical challenges and project progress.
- Promote knowledge sharing through code reviews, workshops, and documentation.
- Design and manage scalable solutions on AWS, leveraging cloud-native tools and best practices.
- Work with large-scale datalake architectures to support data-driven applications.
- Assist in monitoring and maintaining deployed models and services.
- Communicate technical progress, challenges, and results clearly within the team.
- Contribute to internal documentation and project updates
- 4+ years of experience in AI/ML model design, training, and deployment in production environments.
- Proven expertise in building and optimizing models, including LLMs, VLMs, and other deep learning architectures.
- Exposure to transfer learning, self-supervised learning, multimodal AI systems and domain generalization.
- Knowledge of retrieval-augmented generation (RAG), diffusion models, or other cutting-edge ML techniques.
- Strong programming skills in Python with solid knowledge of data structures, algorithms, and software engineering best practices.
- Hands-on experience with large-scale datalake architectures and distributed data processing
- Experience with modern ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and MLOps practices (CI/CD, experiment tracking, reproducibility).
- Strong communication, documentation, and presentation skills, with the ability to work across teams and with external partners.
- Ability to stay current with emerging AI research and assess applicability of new methods to real-world problems.
- Bachelor's or master's degree in computer science, computer engineering, statistics, or mathematics
Skills Required
- 4+ years of experience in AI/ML model design, training, and deployment in production environments
- Proven expertise in building and optimizing models, including LLMs, VLMs, and other deep learning architectures
- Strong programming skills in Python with solid knowledge of data structures, algorithms, and software engineering best practices
- Experience with modern ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and MLOps practices
- Bachelor's or master's degree in computer science, computer engineering, statistics, or mathematics
What We Do
At Precision AI we are on a mission to accelerate artificial intelligence based farming practices to create healthier, happier, and more profitable farms. By leveraging our advanced drones and custom-built AI technology, we can take crop production decisions from a whole field to an individual plant level. This type of decision-making transforms an industry that has been reliant on larger and broader technology for decades. The outcome of our solutions is integrated into the agricultural technology of today and helps craft the machines of tomorrow that will feed the world. Precision AI was founded in 2017 with headquarters in Regina, Saskatchewan. We are scaling rapidly with an elite global team solving the agriculture challenges of farms around the world.









