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Machine Learning Ops (mlops) Developer
Build foundation models and generative AI tools for the AEC industry.
Toronto
Mid-Level
1 month ago
✨ About The Role
- The role involves collaborating with other engineers to develop scalable data pipelines and architectures focused on MLOps best practices for large language models.
- Responsibilities include supporting tasks related to data collection, analysis, content understanding, storage, and processing.
- The developer will write code for model training, testing, and deployment, ensuring the accuracy and performance of machine learning models.
- The position requires organizing and processing large batches of text and geometric data.
- Communication of findings through quantitative data analysis and qualitative visuals is an important aspect of the job.
âš¡ Requirements
- A master's degree in Machine Learning, Artificial Intelligence, Mathematics, Statistics, Computer Science, or a related field is essential for this role.
- Candidates should have at least 3 years of experience in machine learning engineering or a related field.
- Proficiency in training deep neural networks, such as CNNs and transformers, is required, along with experience in at least one deep learning framework like PyTorch or TensorFlow.
- Familiarity with large language models (LLMs) and related technologies, including embedding models and vector databases, is crucial.
- A strong understanding of data modeling, architecture, and processing using varied data representations, including 2D/3D geometry, is necessary.
About PlanGrid
Mobile applications for the construction industry.