Senior Machine Learning Engineering Leader
1 day ago
Capital One is seeking a highly skilled Senior Machine Learning Engineering Leader to provide technical leadership to engineering teams dedicated to productionizing machine learning applications and systems at scale.
About the Role:
- In this role, you will participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.
- You will serve as a technical domain expert in machine learning, guiding machine learning architectural design decisions, developing and reviewing model and application code, and ensuring high availability and performance of our machine learning applications.
- This role offers a unique opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering, while mentoring other engineers and further developing your technical knowledge and skills.
- Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams.
- Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems.
- Lead large-scale ML initiatives with the customer in mind.
- Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.
- Optimize data pipelines to feed ML models.
- Use programming languages like Python, Scala, C/C++.
- Leverage compute technologies such as Dask and RAPIDS.
- Evangelize best practices in all aspects of the engineering and modeling lifecycles.
- Help recruit, nurture, and retain top engineering talent.
- Bachelor's degree.
- At least 10 years of experience designing and building data-intensive solutions using distributed computing.
- At least 6 years of experience programming in C, C++, Python, or Scala.
- At least 3 years of experience with the full ML development lifecycle using modern technology in a business critical setting.
- At least 2 years of experience using Dask, RAPIDS, or in High Performance Computing.
- At least 2 years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn).
- Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
- 3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models.
- 8+ years of experience within a large/data-intensive multi-line business environment.
- Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure/platforms.
- Ability to communicate complex technical concepts clearly to a variety of audiences.
- ML industry impact through conference presentations, papers, blog posts, or open source contributions.
- Ability to attract and develop high-performing software engineers with an inspiring leadership style.
We offer a competitive salary range of $170,000 - $220,000 per year, depending on experience. In addition, we provide a comprehensive benefits package, including health insurance, retirement savings plan, and paid time off.
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