Machine Learning Engineer 4, Machine Learning Foundations

What you'll do

• Design, build, and deliver ML models and components to solve real-world business problems.
• Inform infrastructure decisions regarding model selection, data features, hyperparameter tuning, and validation.
• Write and test application code to develop, validate, and automate the deployment of ML models.
• Retrain, maintain, and monitor machine learning models in production environments.
• Build and leverage cloud-based architectures and platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed data into machine learning models.
• Implement CI/CD best practices, including test automation and monitoring, for ML models and application code.
• Ensure all code and models follow best practices for Responsible and Explainable AI and risk governance.

What we're looking for

• Bachelor's Degree or higher in Computer Science, Machine Learning, or a related quantitative field.
• At least 4 years of experience programming with Python, Java, Golang, or C++.
• At least 4 years of Machine Learning experience using PyTorch or Tensorflow and libraries like Pandas, NumPy, and Scikit-learn.
• At least 4 years of experience using and operating large scale distributed systems like Spark or Ray to prepare AI data.
• At least 2 years of experience deploying and operating ML solutions in production using cloud services (AWS, GCP, Azure) and Kubernetes.
• Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field (preferred).
• 3+ years of experience optimizing ML algorithms, configurations, and infrastructure (preferred).
• 3+ years of experience following software development best practices including source control, testing, code reviews, and CI/CD (preferred).