Machine Learning Architect

6 days ago


New York, New York, United States Capital One Full time

We are seeking a seasoned Senior Machine Learning Engineer to join our Agile team dedicated to productionizing machine learning applications at scale.

You will participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.

Your focus will be on machine learning architectural design, developing and reviewing model and application code, and ensuring high availability and performance of our machine learning applications.

You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

Key Responsibilities:

  • Design, Build, and Deliver Machine Learning Models: Collaborate with Product and Data Science teams to create innovative machine learning solutions that solve real-world business problems.
  • Inform Infrastructure Decisions: Use your expertise in machine learning modeling techniques to make informed decisions about infrastructure investments.
  • Solve Complex Problems: Write and test application code, develop and validate machine learning models, and automate tests and deployment.
  • Collaborate as Part of a Cross-Functional Team: Work with our Agile team to create software that enables cutting-edge big data and machine learning applications.
  • Retrain, Maintain, and Monitor Models: Ensure our machine learning models perform optimally in production.
  • Leverage Cloud-Based Architectures: Utilize cloud-based technologies to deliver optimized machine learning models at scale.
  • Construct Optimized Data Pipelines: Develop efficient data pipelines to feed machine learning models.
  • Ensure Continuous Integration and Deployment: Implement continuous integration and deployment best practices to ensure successful deployment of machine learning models and application code.
  • Implement Responsible and Explainable AI: Ensure all code is well-managed, models are well-governed from a risk perspective, and machine learning follows best practices in responsible and explainable AI.
  • Programming Languages: Utilize programming languages like Python, Scala, or Java.

Requirements:

  • Bachelor's Degree: A degree in a related 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 an industry-recognized machine learning framework.
  • Model Productionization: At least 1 year of experience productionizing, monitoring, and maintaining models.

Preferred Qualifications:

  • Machine Learning Systems: 1+ years of experience building, scaling, and optimizing machine learning systems.
  • Data Gathering and Preparation: 1+ years of experience with data gathering and preparation for machine learning models.
  • Performant Code Development: 2+ years of experience developing performant, resilient, and maintainable code.
  • Public Cloud Experience: Experience developing and deploying machine learning solutions in a public cloud.
  • Advanced Degrees: A master's or doctoral degree in a related field such as computer science, electrical engineering, or mathematics.
  • Distributed File Systems: 3+ years of experience with distributed file systems or multi-node database paradigms.
  • Open-Source Contributions: Contributed to open-source machine learning software.
  • Research Papers: Authored/co-authored a paper on a machine learning technique, model, or proof of concept.
  • Production-Ready Data Pipelines: 3+ years of experience building production-ready data pipelines that feed machine learning models.

Compensation:

  • New York City (Hybrid On-Site): $165,100 - $188,500 per year.


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