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# AI/ML Engineer

- **Company:** Triunity Software
- **Location:** San Francisco, CA, United States
- **Salary:** $100,000.0 - $110,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Cloud Computing, Data Cleansing, Python (Programming Language), Machine Learning, Systems Development Life Cycle, Tensorflow, Feature Engineering, Pytorch, Deep Learning, Model Validation, Scikit Learn, Information Technology, Data Management, Machine Learning Operations, Data Pipelines
- **Published:** November 2, 2026
- **Apply:** https://www.careerbuilder.com/job-details/ai-ml-engineer-san-francisco-ca--287b12dd-e006-41ac-a0fe-c7df57b0e03d

## About the Role

Artificial Intelligence (AI), Health Insurance, Training/Teaching, Machine Learning, Artificial Intelligence (AI), Cross-Functional, Data Management, Scalable System Development, Data Modeling, Performance Modeling, * Bachelor's or Master's degree in Computer Science, Data Science, or a related field

 * Proven experience building and deploying machine learning or deep learning models
 * Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn
 * Experience with cloud platforms (AWS, Azure, or GCP) and MLOps practices
 * Strong understanding of data preprocessing, feature engineering, and model evaluation
 * Familiarity with NLP, computer vision, or generative AI is a strong asset
 * Excellent problem-solving skills and ability to work in an agile environment

## Description

Triunity Software is looking for a talented and driven AI/ML Engineer to join our growing team in Calgary, AB. This is an exciting opportunity to work on cutting-edge artificial intelligence and machine learning solutions that make a real impact. If you're passionate about turning data into intelligent systems, we want to hear from you!, * Design, develop, and deploy machine learning models and AI-driven solutions

 * Collaborate with cross-functional teams to identify and scope AI/ML opportunities
 * Build and maintain scalable data pipelines and model training infrastructure
 * Evaluate and optimize model performance using relevant metrics and testing frameworks
 * Research and implement state-of-the-art ML algorithms and techniques
 * Monitor deployed models and iterate based on real-world performance data
 * Document technical processes, architectures, and model specifications