PatternAI
Posted 75 days agoVerified live 1d ago
Machine Learning Engineer
Brief overview
Remote
3+ yrsMinimum
Machine LearningStatisticsPythonSQLApache SparkPandasScikit-LearnXGBoostPyTorchKerasTensorFlowConvolutional Neural Networks (CNNs)Recurrent Neural Networks (RNN)Long Short-Term Memory Networks (LSTMs)Machine Learning Cloud ServicesProduction Machine Learning SystemsModel Monitoring
About the company
PatternAIpatternai.in
An research & exploring new mediums of thought and expanding the imaginative powers of the human species at subconscious space..
Job description
Summary
PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. They are seeking an outstanding ML Engineer to join their data team and help build out best-in-class machine learning solutions on their platform, powering innovative solutions in marketing & sales and commercial analytics.
Responsibilities
- Build and deploy the ML pipelines that power PatternAI’s machine learning platform
- Manage MLOps infrastructure to monitor and optimize models
Skills
- 3+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist
- Proficiency across topics in machine learning and statistics
- Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas)
- Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services
- Familiarity with CNNs, RNN, LSTMs, and the latest research trends
- Experience implementing, deploying, and maintaining production machine learning systems
- Experience monitoring and optimizing model performance
- Experience with Linux, Docker and AWS, and basic development operations
- Advanced degree in computer science, mathematics, statistics or related area of study strongly preferred
Qualifications
Must Haves
- 3+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist
- Proficiency across topics in machine learning and statistics
- Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas)
- Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services
- Familiarity with CNNs, RNN, LSTMs, and the latest research trends
- Experience implementing, deploying, and maintaining production machine learning systems
- Experience monitoring and optimizing model performance
- Experience with Linux, Docker and AWS, and basic development operations
Nice to Haves
- Advanced degree in computer science, mathematics, statistics or related area of study strongly preferred
