Job Description

Salary: $132,000 - 222,100 per year Requirements:

• I possess a Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience).
• I have 8-10 years of experience in building and maintaining infrastructure for highly available, scalable, and performant distributed systems.
• I have proven expertise with cloud-native technologies (AWS, GCP, Azure) and Kubernetes-based deployments.
• I have hands-on experience running ML training and inference with Ray, including Ray Train/Tune for distributed training and Ray Serve for production inference, encompassing autoscaling, fault tolerance, observability, and multi-tenant operations.
• I have a deep understanding of networking, security, authentication, and identity management in distributed/cloud environments.
• I have hands-on experience with observability stacks (Prometheus, Grafana, OpenTelemetry, etc.).
• I possess strong coding skills in Go and/or Python; familiarity with other systems-level languages is a plus.
• I have knowledge of Linux internals, containers, and storage systems.
• Experience optimizing for GPU/accelerator integration (NVIDIA, AMD, TPU, etc.) is highly desirable.

Responsibilities:

• I will design and scale services to orchestrate AI/ML clusters across cloud and on-premises environments, supporting VM and Kubernetes-based deployments, including Ray clusters for distributed training and online inference.
• I will develop and enhance intelligent scheduling and resource management systems for heterogeneous compute clusters (CPU, GPU, accelerators).
• I will integrate Ray Train/Tune for large-scale distributed training workflows and Ray Serve for low-latency, autoscaled inference, as well as build platform hooks for observability, canary/A-B rollouts, and fault tolerance.
• I will create features that improve reliability, performance, observability, and cost-efficiency of AI workloads at scale.
• I will enhance the control plane to support secure multi-tenancy and enterprise-grade governance.
• I will implement systems for container management, dependency resolution, and large-scale model distribution.
• I will collaborate with ML researchers, applied scientists, and distributed systems engineers to drive platform innovation.
• I will provide production support and work closely with field teams to address infrastructure issues.

Technologies:

• AI
• AWS
• Azure
• Cloud
• GCP
• Grafana
• Support
• Kubernetes
• Linux
• Prometheus
• Python
• Security
• LLM
• Machine Learning

More:

At eBay, we are not merely a global leader in ecommerce; we are transforming how the world shops and sells. Our platform empowers millions of buyers and sellers across more than 190 markets. We are dedicated to pushing the limits and making our mark as we reshape the future of ecommerce for enthusiasts.

Our customers guide our direction, authenticity flourishes, bold ideas are encouraged, and everyone is invited to bring their unique selves to work each day. Together, we sustain the future of our customers, our company, and our planet.

Join our dedicated team of thinkers, innovators, and dreamers — and help us connect individuals and build communities to create economic opportunities for everyone.

I look forward to exploring your potential contributions to our team.

last updated 44 week of 2025

Job Tags

Full time,

Similar Jobs