Software Engineer Graduate - 2027 Start

Responsibilities

• Design and build ML platform orchestration capabilities for jobs, services, and stateful workloads.
• Develop multi-tenant resource, quota, priority, preemption, fair-sharing, elasticity, and cross-cluster scheduling systems.
• Improve GPU utilization and cost efficiency through resource pooling and FinOps.
• Build model-serving lifecycle capabilities including distribution, deployment, upgrades, rollback, autoscaling, multi-cluster operation, and disaster recovery.
• Develop topology-aware scheduling, KV Cache affinity, intelligent request routing, and QoS/SLA management for disaggregated serving clusters.

Requirements

• Completing or recently completed a PhD in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field.
• Proficiency in at least one of Go, C++, or Python, with a foundation in data structures, algorithms, and software engineering principles.
• Familiarity with Linux, operating systems, computer networks, concurrent programming, and distributed systems.
• Hands-on exploratory ability using source code, metrics, logs, profiling, and experiments.
• A systematic and quantitative approach to problem solving, including defining measurements, testing hypotheses, and validating improvements.
• Demonstrated ownership and collaboration through coursework, research, internships, open-source contributions, or engineering projects.
• Preferred experience with Kubernetes, container runtimes, resource scheduling, quota management, multi-tenant systems, or FinOps.
• Preferred contributions to infrastructure projects such as Kubernetes, Volcano, Koordinator, or OpenKruise.
• Preferred experience with vLLM, SGLang, Triton, KServe, Ray Serve, KV Cache, Continuous Batching, Prefill/Decode disaggregation, or model parallelism.
• Preferred experience with online services, gateways, traffic management, autoscaling, performance optimization, highly available distributed systems, GPU/NPU programming, heterogeneous resource scheduling, model distribution, or inference performance analysis.

Benefits

• Graduate opportunity with an onboarding date that must be committed to by the end of the year; candidates should state availability and graduation date in their resume.