Machine Learning Engineer Intern AML
Core
Design and build ML platform orchestration capabilities, multi-tenant resource systems, and online model-serving lifecycle management using Kubernetes and container runtimes.
Role type
Machine Learning Engineer Intern (Infrastructure/Platform)
Builds
ML platform orchestration, multi-tenant resource systems, online model-serving lifecycle, and disaggregated serving clusters.
Domain
Cloud Infrastructure, Distributed Systems, Machine Learning Operations (MLOps)
Deliverable
infrastructure
Required skills
Go, C++, Python, Linux, distributed systems, concurrent programming, data structures, algorithms, system debugging, metrics analysis, hypothesis testing
Preferred skills
Kubernetes, container runtimes, resource scheduling, FinOps, vLLM, SGLang, Triton, KServe, Ray Serve, KV Cache, Continuous Batching, model parallelism, inference performance analysis
Technologies
Kubernetes, Operators, container runtimes, vLLM, SGLang, Triton, KServe, Ray Serve
Responsibilities
Design and build ML platform orchestration capabilities using Kubernetes Operators and container runtimes; Build multi-tenant resource and quota systems; Improve GPU utilization and cost efficiency through resource pooling and FinOps; Develop online model-serving lifecycle orchestration; Develop serving orchestration and traffic management for disaggregated serving clusters.
Seniority
Intern
