Director, Machine Learning Engineer Job at Hobbsnews in San Francisco
Hobbsnews, San Francisco, CA, United States
Director, Machine Learning Engineer
As a Capital One Machine Learning Engineer, you will provide technical leadership to Agile teams dedicated to productionizing machine learning applications and systems at scale. You will participate in detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.
What you’ll do in the role:
Deliver machine learning models and software components that solve challenging business problems in the financial services industry, working in collaboration with product, architecture, engineering, and data science teams.
Drive the creation and evolution of machine learning models and software that enable state‑of‑the‑art intelligent systems.
Lead large‑scale machine learning initiatives with the customer in mind.
Leverage cloud‑based architectures and technologies to deliver optimized machine learning models at scale.
Optimize data pipelines to feed machine learning models.
Use programming languages like Python, Scala, or Java.
Evangelize best practices in all aspects of the engineering and modeling lifecycles.
Recruit, nurture, and retain top engineering talent.
Basic Qualifications:
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 with Python, Scala, or Java.
At least 5 years of people management experience.
At least 3 years of experience with the full machine learning development lifecycle using modern technology in a business‑critical setting.
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 machine learning models.
8+ years of experience within a large data‑intensive multi‑line business environment.
5+ years of experience leading software engineering teams.
Expertise designing, implementing, and scaling complex production‑ready data pipelines for machine learning models.
Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure or platforms.
Ability to communicate complex technical concepts clearly to a variety of audiences.
Highly developed interpersonal, presentation, and communications skills.
Machine learning industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
Ability to attract and develop high‑performing software engineers with an inspiring leadership style.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Capital One is an equal opportunity employer (EOE, including disability/vet).
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In Summary: As a Capital One Machine Learning Engineer, you will provide technical leadership to Agile teams dedicated to productionizing machine learning applications and systems at scale . What you’ll do in the role: Deliver machine learning models and software components that solve challenging business problems in the financial services industry .
En Español: Director, Ingeniero de Aprendizaje Automático Como ingeniero de aprendizaje automático Capital One, usted proporcionará un liderazgo técnico a los equipos ágiles dedicados a la producción en escala de aplicaciones y sistemas de aprendizado automático. Participará en el diseño técnico detallado, desarrollo e implementación de aplicaciones de aprendizaje automático utilizando plataformas tecnológicas existentes y emergentes. Lo que hará en la función: entregar modelos y componentes de software de aprendizado automático que resuelvan problemas empresariales desafiantes en la industria de los servicios financieros, trabajando en colaboración con equipos de producto, arquitectura, ingeniería y ciencias de datos. Impulsará la creación y evolución de modelos y programas de enseñanza automática que permitan desarrollar sistemas inteligentes modernos. Dirigirá iniciativas a gran escala para aprender máquina teniendo en cuenta al cliente. Aprovechará las arquitecturas y tecnologías basadas en la nube para ofrecer modelos optimizados de machine learning a escala. Optimizará canalizaciones de datos para alimentar modelos de aprendizage automático. Utilice lenguajes de programación como Python, Scala o Java. Utilicará mejores prácticas en todos los aspectos del ciclo de vida de ingeniería e ingeniería. Reclutar, nutrir y retener una plataforma de conocimiento avanzada.
As a Capital One Machine Learning Engineer, you will provide technical leadership to Agile teams dedicated to productionizing machine learning applications and systems at scale. You will participate in detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.
What you’ll do in the role:
Deliver machine learning models and software components that solve challenging business problems in the financial services industry, working in collaboration with product, architecture, engineering, and data science teams.
Drive the creation and evolution of machine learning models and software that enable state‑of‑the‑art intelligent systems.
Lead large‑scale machine learning initiatives with the customer in mind.
Leverage cloud‑based architectures and technologies to deliver optimized machine learning models at scale.
Optimize data pipelines to feed machine learning models.
Use programming languages like Python, Scala, or Java.
Evangelize best practices in all aspects of the engineering and modeling lifecycles.
Recruit, nurture, and retain top engineering talent.
Basic Qualifications:
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 with Python, Scala, or Java.
At least 5 years of people management experience.
At least 3 years of experience with the full machine learning development lifecycle using modern technology in a business‑critical setting.
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 machine learning models.
8+ years of experience within a large data‑intensive multi‑line business environment.
5+ years of experience leading software engineering teams.
Expertise designing, implementing, and scaling complex production‑ready data pipelines for machine learning models.
Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure or platforms.
Ability to communicate complex technical concepts clearly to a variety of audiences.
Highly developed interpersonal, presentation, and communications skills.
Machine learning industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
Ability to attract and develop high‑performing software engineers with an inspiring leadership style.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Capital One is an equal opportunity employer (EOE, including disability/vet).
#J-18808-Ljbffr
In Summary: As a Capital One Machine Learning Engineer, you will provide technical leadership to Agile teams dedicated to productionizing machine learning applications and systems at scale . What you’ll do in the role: Deliver machine learning models and software components that solve challenging business problems in the financial services industry .
En Español: Director, Ingeniero de Aprendizaje Automático Como ingeniero de aprendizaje automático Capital One, usted proporcionará un liderazgo técnico a los equipos ágiles dedicados a la producción en escala de aplicaciones y sistemas de aprendizado automático. Participará en el diseño técnico detallado, desarrollo e implementación de aplicaciones de aprendizaje automático utilizando plataformas tecnológicas existentes y emergentes. Lo que hará en la función: entregar modelos y componentes de software de aprendizado automático que resuelvan problemas empresariales desafiantes en la industria de los servicios financieros, trabajando en colaboración con equipos de producto, arquitectura, ingeniería y ciencias de datos. Impulsará la creación y evolución de modelos y programas de enseñanza automática que permitan desarrollar sistemas inteligentes modernos. Dirigirá iniciativas a gran escala para aprender máquina teniendo en cuenta al cliente. Aprovechará las arquitecturas y tecnologías basadas en la nube para ofrecer modelos optimizados de machine learning a escala. Optimizará canalizaciones de datos para alimentar modelos de aprendizage automático. Utilice lenguajes de programación como Python, Scala o Java. Utilicará mejores prácticas en todos los aspectos del ciclo de vida de ingeniería e ingeniería. Reclutar, nutrir y retener una plataforma de conocimiento avanzada.