Lead Machine Learning Engineer (Enterprise Platforms Technology) Job at Capital
Capital One National Association, New York, NY, United States
Lead Machine Learning Engineer (Enterprise Platforms Technology)
As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure 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.
Enterprise Platforms Technology (EPTech) comprises many of Capital One’s most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices.
What you’ll do in the role:
Design, build, and deliver ML models and components that solve real‑world business problems while collaborating with Product and Data Science teams.
Make ML infrastructure decisions using your understanding of modeling techniques and issues, including choice of model, data, feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation.
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
Collaborate as part of a cross‑functional Agile team to create and enhance software that enables state‑of‑the‑art big data and ML applications.
Retrain, maintain, and monitor models in production.
Leverage or build cloud‑based architectures, technologies, and platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
Ensure all code is well‑managed to reduce vulnerabilities, models are well‑governed from a risk perspective, and ML follows Responsible and Explainable AI best practices.
Use programming languages such as Python, Scala, or Java.
Basic Qualifications
Bachelor’s degree.
At least 6 years of experience designing and building data‑intensive solutions using distributed computing (internship experience does not apply).
At least 4 years of experience programming with Python, Scala, or Java.
At least 2 years of experience building, scaling, and optimizing ML systems.
Preferred Qualifications
Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
3+ years of experience building production‑ready data pipelines that feed ML models.
3+ years of on‑the‑job experience with an industry‑recognized ML framework such as scikit‑learn, PyTorch, Dask, Spark, or TensorFlow.
2+ years of experience developing performant, resilient, and maintainable code.
2+ years of experience with data gathering and preparation for ML models.
2+ years of people‑leader experience.
1+ year of experience leading teams developing ML solutions using industry best practices, patterns, and automation.
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or GCP.
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.
ML industry impact through conference presentations, papers, blog posts, open‑source contributions, or patents.
At this time, Capital One will not sponsor a new applicant for employment authorization or offer any immigration‑related support for this position.
New York, NY: $211,000 – $240,800 for Lead Machine Learning Engineer. Other locations are subject to the pay range associated with that location.
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.
Capital One is an equal‑opportunity employer (EOE, including disability/veteran). Capital One promotes a drug‑free workplace.
RecruitingAccommodation@capitalone.com
Careers@capitalone.com
Capital One does not provide, endorse, nor guarantee and is not liable for third‑party products, services, educational tools or other information available through this site.
#J-18808-Ljbffr
In Summary: As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale . You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance .
En Español: Ingeniero líder de aprendizaje automático (Tecnología de plataformas empresariales) Como ingeniero de Machine Learning Capital One (MLE), formarás parte de un equipo ágil dedicado a la producción de aplicaciones y sistemas de machine learning en escala. Participarás en el diseño técnico detallado, desarrollo e implementación de las aplicaciones de machine Learning utilizando plataformas tecnológicas existentes y emergentes. Te centrarás en diseño arquitectónico del aprendizaje automatico, desarrollará y revisará el modelo y código de aplicación y garantizará una alta disponibilidad y rendimiento de nuestras aplicaciones. Tendrás la oportunidad de aprender continuamente y aplicar las últimas innovaciones y mejores prácticas en ingeniería de máquina. Juguemos un papel esencial en el establecimiento de prácticas para construir soluciones tecnológicas a través de la empresa, al tiempo que ofrecemos capacidades que ejemplifican esas prácticas. Resolverá problemas complejos mediante la escritura y prueba de aplicaciones, y validará modelos ML y componentes que resuelvan problemas comerciales reales mientras colaboran con equipos Product and Data Science. Tomar decisiones sobre infraestructura ML utilizando su comprensión de las técnicas y cuestiones de modelado, incluida la elección del modelo, los datos, la selección de características, la capacitación, el ajuste de hiperparámetros, la dimensionalidad, el sesgo/varianza y la validación. Diseñar, desarrollar y entregar modelos ML que solucionen problemas empresariales realistas colaborando con equipos Tensor Agile multifuncional. Colaborar como parte de un equipo ágil transversal para crear y mejorar software que facilite las aplicaciones Big-Data y Machine Learning. Reconocer, mantener y monitorear modelos inteligentes en pieza de datos básicos o sistemas operativos basados en código base en Python. Otras ubicaciones están sujetas al rango salarial asociado a esa ubicación. Capital One ofrece un conjunto completo, competitivo e inclusivo de beneficios para la salud, financieros y otros que apoyan su bienestar total. Obtenga más información en el sitio web de Capital One Careers. Capital one es un empleador con igualdad de oportunidades (EOE, incluida discapacidad/veteranos). Capital One promueve un lugar de trabajo libre de drogas. RecruitingAccommodation@capitalone.com Careers@capitals.com Capital One no proporciona, respalda ni garantiza productos, servicios, herramientas educativas u otra información de terceros disponibles a través de este sitio. #J-18808-Ljbffr
As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure 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.
Enterprise Platforms Technology (EPTech) comprises many of Capital One’s most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices.
What you’ll do in the role:
Design, build, and deliver ML models and components that solve real‑world business problems while collaborating with Product and Data Science teams.
Make ML infrastructure decisions using your understanding of modeling techniques and issues, including choice of model, data, feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation.
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
Collaborate as part of a cross‑functional Agile team to create and enhance software that enables state‑of‑the‑art big data and ML applications.
Retrain, maintain, and monitor models in production.
Leverage or build cloud‑based architectures, technologies, and platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
Ensure all code is well‑managed to reduce vulnerabilities, models are well‑governed from a risk perspective, and ML follows Responsible and Explainable AI best practices.
Use programming languages such as Python, Scala, or Java.
Basic Qualifications
Bachelor’s degree.
At least 6 years of experience designing and building data‑intensive solutions using distributed computing (internship experience does not apply).
At least 4 years of experience programming with Python, Scala, or Java.
At least 2 years of experience building, scaling, and optimizing ML systems.
Preferred Qualifications
Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
3+ years of experience building production‑ready data pipelines that feed ML models.
3+ years of on‑the‑job experience with an industry‑recognized ML framework such as scikit‑learn, PyTorch, Dask, Spark, or TensorFlow.
2+ years of experience developing performant, resilient, and maintainable code.
2+ years of experience with data gathering and preparation for ML models.
2+ years of people‑leader experience.
1+ year of experience leading teams developing ML solutions using industry best practices, patterns, and automation.
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or GCP.
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.
ML industry impact through conference presentations, papers, blog posts, open‑source contributions, or patents.
At this time, Capital One will not sponsor a new applicant for employment authorization or offer any immigration‑related support for this position.
New York, NY: $211,000 – $240,800 for Lead Machine Learning Engineer. Other locations are subject to the pay range associated with that location.
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.
Capital One is an equal‑opportunity employer (EOE, including disability/veteran). Capital One promotes a drug‑free workplace.
RecruitingAccommodation@capitalone.com
Careers@capitalone.com
Capital One does not provide, endorse, nor guarantee and is not liable for third‑party products, services, educational tools or other information available through this site.
#J-18808-Ljbffr
In Summary: As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale . You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance .
En Español: Ingeniero líder de aprendizaje automático (Tecnología de plataformas empresariales) Como ingeniero de Machine Learning Capital One (MLE), formarás parte de un equipo ágil dedicado a la producción de aplicaciones y sistemas de machine learning en escala. Participarás en el diseño técnico detallado, desarrollo e implementación de las aplicaciones de machine Learning utilizando plataformas tecnológicas existentes y emergentes. Te centrarás en diseño arquitectónico del aprendizaje automatico, desarrollará y revisará el modelo y código de aplicación y garantizará una alta disponibilidad y rendimiento de nuestras aplicaciones. Tendrás la oportunidad de aprender continuamente y aplicar las últimas innovaciones y mejores prácticas en ingeniería de máquina. Juguemos un papel esencial en el establecimiento de prácticas para construir soluciones tecnológicas a través de la empresa, al tiempo que ofrecemos capacidades que ejemplifican esas prácticas. Resolverá problemas complejos mediante la escritura y prueba de aplicaciones, y validará modelos ML y componentes que resuelvan problemas comerciales reales mientras colaboran con equipos Product and Data Science. Tomar decisiones sobre infraestructura ML utilizando su comprensión de las técnicas y cuestiones de modelado, incluida la elección del modelo, los datos, la selección de características, la capacitación, el ajuste de hiperparámetros, la dimensionalidad, el sesgo/varianza y la validación. Diseñar, desarrollar y entregar modelos ML que solucionen problemas empresariales realistas colaborando con equipos Tensor Agile multifuncional. Colaborar como parte de un equipo ágil transversal para crear y mejorar software que facilite las aplicaciones Big-Data y Machine Learning. Reconocer, mantener y monitorear modelos inteligentes en pieza de datos básicos o sistemas operativos basados en código base en Python. Otras ubicaciones están sujetas al rango salarial asociado a esa ubicación. Capital One ofrece un conjunto completo, competitivo e inclusivo de beneficios para la salud, financieros y otros que apoyan su bienestar total. Obtenga más información en el sitio web de Capital One Careers. Capital one es un empleador con igualdad de oportunidades (EOE, incluida discapacidad/veteranos). Capital One promueve un lugar de trabajo libre de drogas. RecruitingAccommodation@capitalone.com Careers@capitals.com Capital One no proporciona, respalda ni garantiza productos, servicios, herramientas educativas u otra información de terceros disponibles a través de este sitio. #J-18808-Ljbffr