Senior Kubernetes Engineer - Machine Learning Platform

JOB DESCRIPTION

What We Do

At Goldman Sachs, our Engineers don’t just make things – we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets.

Engineering, which is comprised of our Technology Division and global strategists’ groups, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Start here.

Who We Look For

Goldman Sachs Engineers are innovators and problem-solvers, building solutions in risk management, big data, mobile and more. We look for creative collaborators who evolve, adapt to change, and thrive in a fast-paced global environment.

We are seeking a talented and experienced Kubernetes Engineer to join our Data Science and Machine Learning Platform team to build and implement operators and services on Kubernetes in the public cloud to support our AI/ML agenda. As part of our team, you will collaborate with multiple teams across the broader Engineering Organization to re-imagine how we leverage Kubernetes as part of the end-to-end model development lifecycle. This is an incredible opportunity to drive impactful and high-profile business value while working with the latest and greatest ML/AI frameworks and technologies.

Key Responsibilities:

• Develop and implement Kubernetes operators and services tailored for our Data Science and Machine Learning Platform, including, but not limited to:
• Workbench environments for model development & training, supporting both CPU and GPU based distributed computing
• Workflow for ML Pipelines
• Batch & Real-Time inferencing
• Model Monitoring
• Partner with the Firmwide Kubernetes team to ensure the base cluster on which we build our components meets all required pre-requisites
• Work with the ArgoCD tool to manage GitOps-based continuous deployment of Kubernetes applications and ensure reliable application releases
• Write clean, efficient, and maintainable code in Python and/or Go to implement and/or extend the functionality of open-source Kubernetes operators and services
• Mentor both junior as well as experience engineers on Kubernetes and MLOps best practices
• Partner with the Firmwide Kubernetes team to troubleshoot and debug issues in the Kubernetes infrastructure, containers, and related components, ensuring high system availability and performance
• Stay up to date with the latest industry trends, tools, and technologies related to Kubernetes, MLOps, and cloud computing

Basic Qualifications:

• Bachelor’s (or equivalent experience) or Master's degree in Computer Science, Engineering or related field
• 6+ years of experience delivering and maintaining software solutions in production environments
• 4+ years of experience in Python and/or Go programming for machine learning and/or application development to support machine learning
• 3+ years of experience implementing Kubernetes operators and/or services that support the Model Development Lifecycle
• 3+ years of experience with Unix-based systems and working with command-line tools

Preferred Qualifications:

• Previous experience working with Kubernetes on public cloud platforms such as GCP
• Hands-on experience with ArgoCD for GitOps-based deployment of Kubernetes applications
• Strong problem-solving skills and the ability to analyze complex systems and infrastructure issues
• Excellent communication and collaboration skills, with the ability to work effectively in a team environment
• Proactive and self-driven mindset, with a passion for continuous learning and personal development

ABOUT GOLDMAN SACHS

At Goldman Sachs, we commit our people, capital, and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do.

We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Learn more about our culJOB DESCRIPTION

What We Do

At Goldman Sachs, our Engineers don’t just make things – we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets.

Engineering, which is comprised of our Technology Division and global strategists’ groups, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Start here.

Who We Look For

Goldman Sachs Engineers are innovators and problem-solvers, building solutions in risk management, big data, mobile and more. We look for creative collaborators who evolve, adapt to change, and thrive in a fast-paced global environment.

We are seeking a talented and experienced Kubernetes Engineer to join our Data Science and Machine Learning Platform team to build and implement operators and services on Kubernetes in the public cloud to support our AI/ML agenda. As part of our team, you will collaborate with multiple teams across the broader Engineering Organization to re-imagine how we leverage Kubernetes as part of the end-to-end model development lifecycle. This is an incredible opportunity to drive impactful and high-profile business value while working with the latest and greatest ML/AI frameworks and technologies.

Key Responsibilities:

• Develop and implement Kubernetes operators and services tailored for our Data Science and Machine Learning Platform, including, but not limited to:
• Workbench environments for model development & training, supporting both CPU and GPU based distributed computing
• Workflow for ML Pipelines
• Batch & Real-Time inferencing
• Model Monitoring
• Partner with the Firmwide Kubernetes team to ensure the base cluster on which we build our components meets all required pre-requisites
• Work with the ArgoCD tool to manage GitOps-based continuous deployment of Kubernetes applications and ensure reliable application releases
• Write clean, efficient, and maintainable code in Python and/or Go to implement and/or extend the functionality of open-source Kubernetes operators and services
• Mentor both junior as well as experience engineers on Kubernetes and MLOps best practices
• Partner with the Firmwide Kubernetes team to troubleshoot and debug issues in the Kubernetes infrastructure, containers, and related components, ensuring high system availability and performance
• Stay up to date with the latest industry trends, tools, and technologies related to Kubernetes, MLOps, and cloud computing

Basic Qualifications:

• Bachelor’s (or equivalent experience) or Master's degree in Computer Science, Engineering or related field
• 6+ years of experience delivering and maintaining software solutions in production environments
• 4+ years of experience in Python and/or Go programming for machine learning and/or application development to support machine learning
• 3+ years of experience implementing Kubernetes operators and/or services that support the Model Development Lifecycle
• 3+ years of experience with Unix-based systems and working with command-line tools

Preferred Qualifications:

• Previous experience working with Kubernetes on public cloud platforms such as GCP
• Hands-on experience with ArgoCD for GitOps-based deployment of Kubernetes applications
• Strong problem-solving skills and the ability to analyze complex systems and infrastructure issues
• Excellent communication and collaboration skills, with the ability to work effectively in a team environment
• Proactive and self-driven mindset, with a passion for continuous learning and personal development

ABOUT GOLDMAN SACHS

At Goldman Sachs, we commit our people, capital, and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do.

We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Learn more about our culture, benefits, and people at GS/careers. We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process.

© The Goldman Sachs Group, Inc., 2023. All rights reserved.

Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity.ture, benefits, and people at GS/careers. We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process.

© The Goldman Sachs Group, Inc., 2023. All rights reserved.

Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity.