We are seeking a seasoned Distinguished Engineer - Machine Learning Engineering to join our Machine Learning Experience (MLX) team. As a part of this team, you will play a pivotal role in enhancing our observability and model governance automation capabilities. Your primary focus will be on designing and implementing systems that manage large volumes of model metadata and runtime metrics, enabling automated governance decisions and building a robust observability platform. You will collaborate closely with model and platform teams, utilizing cloud-based architectures and technologies to optimize and deploy ML models at scale.
Key Responsibilities
- Collaborate with cross-functional Agile teams to develop scalable solutions for model governance and observability.
- Design and implement optimized data pipelines to support machine learning models.
- Utilize Python, Scala, or Java to develop and deploy machine learning applications.
- Implement continuous integration and deployment practices to ensure robust model deployment and application code releases.
- Enhance ML platforms through innovative research and development, integrating machine learning into the core of business operations.
Basic Qualifications
- Master's Degree in Computer Science or related field.
- 15+ years of experience in software engineering or solution architecture.
- Extensive experience (10+ years) designing and building data-intensive solutions using distributed computing technologies.
- Proficiency (10+ years) in programming with Python, Go, or Java.
- On-the-job experience (5+ years) with leading ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
- Hands-on experience (5+ years) in productionizing, monitoring, and maintaining machine learning models.
Preferred Qualifications
- Master’s Degree or PhD in Computer Science, Electrical Engineering, Mathematics, or similar field.
- Significant experience (5+ years) building, scaling, and optimizing ML systems.
- Expertise in developing performant, resilient, and maintainable code.
- Experience (5+ years) deploying ML solutions in public cloud environments (AWS, Azure, GCP).
- Proficiency (5+ years) with distributed file systems or multi-node database paradigms.
- Contributions to open-source ML software or authored/co-authored ML-related papers.
- Experience (5+ years) in developing production-ready data pipelines for ML models.
- Proficiency (5+ years) in MLOps using tools like MLFlow or commercial equivalents.
- Experience (2+ years) developing applications using Generative AI technologies.
Additional Information
Capital One is committed to diversity, inclusion, and creating a supportive workplace environment. We offer equal opportunities for all applicants without regard to sex, race, age, disability, or other protected characteristics. We promote a drug-free workplace and comply with applicable laws regarding criminal background inquiries.
For more details about this position or to apply, visit our Capital One Careers page or contact us at [email protected].