Work with large-scale structured and unstructured data, build and continuously improve cutting-edge Machine Learning models for Procore product, business, and operational use cases; Evaluate and train Large Language Models (LLMs), traditional language models such as BERT, and other machine learning models such as XGBoost; Hands-on development, production, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases; Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable, highly differentiating, and high-performing Machine Learning systems, enabling fast model development, low-latency serving, and ease of model quality upkeep
Requirements:
9+ years of industry experience in applied Machine Learning, inclusive Bachelor/Master or Ph.D. in relevant fields; Exceptional written and verbal communication skills; Strong programming ( Python/Java/C++ or equivalent) and data engineering skills; Strong understanding of the machine learning and data science technical ecosystems (e.g., Tensorflow, Pytorch, MLflow, Ray, LangChain, Data Lakehouse (Databricks), Snowflake, SageMaker, Scikit-learn, etc)
Text:
Staff Machine Learning Engineer Work with large-scale structured and unstructured data, build and continuously improve cutting-edge Machine Learning models for Procore product, business, and operational use cases; Evaluate and train Large Language Models (LLMs), traditional language models such as BERT, and other machine learning models such as XGBoost; Hands-on development, production, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases; Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable, highly differentiating, and high-performing Machine Learning systems, enabling fast model development, low-latency serving, and ease of model quality upkeep 9+ years of industry experience in applied Machine Learning, inclusive Bachelor/Master or Ph.D. in relevant fields; Exceptional written and verbal communication skills; Strong programming ( Python/Java/C++ or equivalent) and data engineering skills; Strong understanding of the machine learning and data science technical ecosystems (e.g., Tensorflow, Pytorch, MLflow, Ray, LangChain, Data Lakehouse (Databricks), Snowflake, SageMaker, Scikit-learn, etc)
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