eBay
Join to apply for the
AI Capacity Engineer
role at
eBay Join to apply for the
AI Capacity Engineer
role at
eBay Get AI-powered advice on this job and more exclusive features. At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.
Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.
Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.
Team Role
We are seeking a motivated Capacity Engineer to join our central capacity engineering team for eBay's Marketplaces Core Technology organization supporting our artificial intelligence infrastructure.
As a Capacity Engineer, you will be responsible for analyzing, modeling, and forecasting the infrastructure needs of our organization. Your expertise in capacity engineering and forecasting will play a crucial role in optimizing resource allocation and ensuring efficient utilization of our technology assets. Experience with public and private Kubernetes based clouds, application performance principles, and workload optimization will be highly helpful in this role. The successful candidate will have strong analytical skills, superb communication abilities, and a deep understanding of technology infrastructure.
Responsibilities
Collaborate with Core AI teams across multiple geographies to analyse, plan and execute on AI initiatives. Analyse the AI capacity intake requirements for prioritization and scheduling. Seek out and lead execution of performance optimizations of our AI related assets to ensure efficient use. Scope includes Nvidia SuperPod, On-Prem Kubernetes, Azure, and GCP based clouds Understand key performance metrics and scaling characteristics of LLM, non-LLM AI models Understand key concepts and sizing metrics related to RAG, Vector Search, Grounding Influence customer choice of AI models to improve ROI and cost efficiency Design and build dashboards to support management of AI workloads and infrastructure. Be familiar with GPU relevant metrics and how they are used. Strong experience with grafana, prometheus, thanos and ELK stacks Analyze historical data, trends, and growth patterns to develop accurate capacity models such as compute, network, storage, and platform optimization requirements.and forecasts Collaborate with multi-functional teams to gather relevant information on business objectives, technology requirements, and upcoming projects Evaluate and refine existing capacity engineering processes and methodologies to improve accuracy and efficiency Monitor system performance metrics and utilization levels to identify potential bottlenecks or areas of underutilization. Take ownership and drive for the realization of gains from improving utilization Collaborate with technology partners to understand future technology trends and initiatives, anticipate resource demands, and develop proactive capacity plans Conduct "what-if" scenarios to assess the impact of different business scenarios and help guide decision-making processes Manage capacity for large federated Kubernetes environments on primarily private cloud but including some public cloud. Must be articulate and be able to communicate capacity insights, recommendations, and performance metrics to key partners. Advocate for initiatives that provide clear business value through data.
Qualifications
Bachelor's degree in computer science, information systems, statistics or a related field and 2+ years of experience 2 years of experience in capacity engineering, resource allocation, and forecasting in a technology-intensive environment Specialized experience in AI Strong proficiency with grafana, prometheus, thanos, elastic search and kibana (ELK) Proficiency in Kubernetes. Should understand how applications operate in a k8s environment and have experience running apps in k8s. Strong analytical skills with the ability to analyze complex data sets and identify relevant patterns and trends Familiarity with technology infrastructure components, including Ubuntu linux, servers, databases, networks, storage systems, and cloud platforms Knowledge of recommendation engines concepts and their application in infrastructure management
The base pay range for this position is expected in the range below:
$95,200 - $168,700
Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
If hired, employees will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
Please see the Talent Privacy Notice for information regarding how eBay handles your personal data collected when you use the eBay Careers website or apply for a job with eBay.
eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talent@ebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
The eBay Jobs website uses cookies to enhance your experience. By continuing to browse the site, you agree to our use of cookies. Visit our Privacy Center for more information. Seniority level
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Employment type Full-time Job function
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AI Capacity Engineer
role at
eBay Join to apply for the
AI Capacity Engineer
role at
eBay Get AI-powered advice on this job and more exclusive features. At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.
Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.
Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.
Team Role
We are seeking a motivated Capacity Engineer to join our central capacity engineering team for eBay's Marketplaces Core Technology organization supporting our artificial intelligence infrastructure.
As a Capacity Engineer, you will be responsible for analyzing, modeling, and forecasting the infrastructure needs of our organization. Your expertise in capacity engineering and forecasting will play a crucial role in optimizing resource allocation and ensuring efficient utilization of our technology assets. Experience with public and private Kubernetes based clouds, application performance principles, and workload optimization will be highly helpful in this role. The successful candidate will have strong analytical skills, superb communication abilities, and a deep understanding of technology infrastructure.
Responsibilities
Collaborate with Core AI teams across multiple geographies to analyse, plan and execute on AI initiatives. Analyse the AI capacity intake requirements for prioritization and scheduling. Seek out and lead execution of performance optimizations of our AI related assets to ensure efficient use. Scope includes Nvidia SuperPod, On-Prem Kubernetes, Azure, and GCP based clouds Understand key performance metrics and scaling characteristics of LLM, non-LLM AI models Understand key concepts and sizing metrics related to RAG, Vector Search, Grounding Influence customer choice of AI models to improve ROI and cost efficiency Design and build dashboards to support management of AI workloads and infrastructure. Be familiar with GPU relevant metrics and how they are used. Strong experience with grafana, prometheus, thanos and ELK stacks Analyze historical data, trends, and growth patterns to develop accurate capacity models such as compute, network, storage, and platform optimization requirements.and forecasts Collaborate with multi-functional teams to gather relevant information on business objectives, technology requirements, and upcoming projects Evaluate and refine existing capacity engineering processes and methodologies to improve accuracy and efficiency Monitor system performance metrics and utilization levels to identify potential bottlenecks or areas of underutilization. Take ownership and drive for the realization of gains from improving utilization Collaborate with technology partners to understand future technology trends and initiatives, anticipate resource demands, and develop proactive capacity plans Conduct "what-if" scenarios to assess the impact of different business scenarios and help guide decision-making processes Manage capacity for large federated Kubernetes environments on primarily private cloud but including some public cloud. Must be articulate and be able to communicate capacity insights, recommendations, and performance metrics to key partners. Advocate for initiatives that provide clear business value through data.
Qualifications
Bachelor's degree in computer science, information systems, statistics or a related field and 2+ years of experience 2 years of experience in capacity engineering, resource allocation, and forecasting in a technology-intensive environment Specialized experience in AI Strong proficiency with grafana, prometheus, thanos, elastic search and kibana (ELK) Proficiency in Kubernetes. Should understand how applications operate in a k8s environment and have experience running apps in k8s. Strong analytical skills with the ability to analyze complex data sets and identify relevant patterns and trends Familiarity with technology infrastructure components, including Ubuntu linux, servers, databases, networks, storage systems, and cloud platforms Knowledge of recommendation engines concepts and their application in infrastructure management
The base pay range for this position is expected in the range below:
$95,200 - $168,700
Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
If hired, employees will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
Please see the Talent Privacy Notice for information regarding how eBay handles your personal data collected when you use the eBay Careers website or apply for a job with eBay.
eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talent@ebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
The eBay Jobs website uses cookies to enhance your experience. By continuing to browse the site, you agree to our use of cookies. Visit our Privacy Center for more information. Seniority level
Seniority level Entry level Employment type
Employment type Full-time Job function
Job function Engineering and Information Technology Industries Technology, Information and Internet Referrals increase your chances of interviewing at eBay by 2x Sign in to set job alerts for “Artificial Intelligence Engineer” roles.
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Dallas, TX $140,000.00-$160,000.00 3 weeks ago Texas, United States $48,000.00-$168,000.00 2 weeks ago We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr