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Senior Machine Learning Engineer
2 months ago
We are seeking a highly skilled Senior Machine Learning Engineer to join our team at Capital One Financial Corporation. As a key member of our Agile team, you will be responsible for designing, building, and deploying machine learning applications and systems at scale.
Key Responsibilities- Design and Develop Machine Learning Models: Collaborate with cross-functional teams to design and develop machine learning models that solve real-world business problems.
- Inform Infrastructure Decisions: Use your understanding of machine learning modeling techniques and issues to inform infrastructure decisions, including choice of model, data, and feature selection.
- Solve Complex Problems: Write and test application code, develop and validate machine learning models, and automate tests and deployment.
- Collaborate with Cross-Functional Teams: Work with Agile teams to create and enhance software that enables state-of-the-art big data and machine learning applications.
- Retrain, Maintain, and Monitor Models: Retrain, maintain, and monitor models in production to ensure high availability and performance.
- Leverage Cloud-Based Architectures: Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized machine learning models at scale.
- Construct Optimized Data Pipelines: Construct optimized data pipelines to feed machine learning models.
- Ensure Code Quality and Governance: Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and machine learning follows best practices in Responsible and Explainable AI.
- Bachelor's Degree: A bachelor's degree in a relevant field, such as computer science, electrical engineering, or mathematics.
- Programming Experience: At least 4 years of experience programming with Python, Scala, or Java.
- Data-Intensive Solutions: At least 3 years of experience designing and building data-intensive solutions using distributed computing.
- Machine Learning Frameworks: At least 2 years of experience with industry-recognized machine learning frameworks, such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
- Productionizing Models: At least 1 year of experience productionizing, monitoring, and maintaining models.
- Experience with Cloud Platforms: 1+ years of experience building, scaling, and optimizing machine learning systems on cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Data Gathering and Preparation: 1+ years of experience with data gathering and preparation for machine learning models.
- Developing Performant Code: 2+ years of experience developing performant, resilient, and maintainable code.
- Master's or Doctoral Degree: A master's or doctoral degree in a relevant field, such as computer science, electrical engineering, or mathematics.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well-being. Learn more at the Capital One Careers website.
