Senior Artificial Intelligence Engineer

Role Overview 
The Senior Artificial Intelligence Engineer at Precision AI will play a key role in driving the success of our AI initiatives. This role involves planning and overseeing AI projects, developing and optimizing machine learning models, and ensuring technical excellence across the team. The Senior AI Engineer will mentor junior engineers, guide and track project progress, and manage collaborations with external partners.  
Working closely with AI leaders, junior engineers, and strategic partners, the Senior AI Engineer will help shape both the technical direction and day-to-day execution of Precision AI's AI-driven solutions. 
This role is hybrid working out of our Calgary office.  
Key Responsibilities 
AI Project Leadership 
Plan, design, and oversee AI/ML projects from concept to deployment. Define milestones, monitor progress, and ensure timely delivery. 
Model Development & Innovation 
Build, train, and optimize machine learning models, including LLMs and VLMs. Apply a range of techniques such as transfer learning, fine-tuning, prompt engineering, knowledge distillation, multimodal fusion, and efficient inference methods (quantization, pruning, model compression). Stay ahead of emerging technologies and research papers; evaluate applicability to projects. 
Programming Excellence 
Apply strong foundations in data structures, algorithms, object-oriented programming, and software design patterns to build reliable AI systems. Enforce clean, scalable, and maintainable code through practices like code reviews, 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. 
Mentorship & Team Development 
Guide junior engineers through technical challenges and project progress. Promote knowledge sharing through code reviews, workshops, and documentation. 
Cloud Infrastructure & Data Systems 
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. 
Technical Communication and Partner Management 
Collaborate with research and business partners to align on technical goals. Engage with clients to understand requirements, present progress, and ensure satisfaction. Prepare and deliver impactful presentations on project outcomes and strategic directions. 

Relevant Experience 
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 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. 
Why Join Us? 
Work on cutting-edge AI and computer vision technologies with a talented team. Opportunity to contribute to real-world applications and see your models deployed in production. Support for continuous learning, research, and professional growth. 

---