Software Engineer Graduate
ByteDance
Posted 14 Nov 2026, 05:36 ET
This job at a glance
- Who can apply
- New grads, no experience needed
- Must know
- Machine learningSocial mediaOnboardingPythonC++Go
- Nice to have
- KubernetesSystem design
- Work
- On-site in San Jose
- Pay
- Not stated by the employer.
- Skill demand
- Python66%Machine learning25%Social media19%Onboarding15%of 59 similar entry-level jobs posted in the US this week
- Listed
- Nov 14, 2026 · still open
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About the Role
The Data-AML-Engine Orchestration team at ByteDance builds large-scale machine learning infrastructure powering online model serving across ByteDance products, including TikTok. This role involves developing orchestration, scheduling, and resource management systems connecting heterogeneous compute infrastructure with production ML workloads. You will work on systems impacting GPU utilization, serving latency and availability, infrastructure reliability, and MLE productivity. Opportunities exist to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must commit to an onboarding date by the end of the year.
Key Responsibilities
- Design and build foundational orchestration capabilities for machine learning platforms, including Kubernetes Operators, container runtimes, and lifecycle management for jobs, services, and stateful workloads.
- Build multi-tenant resource and quota systems supporting priorities, preemption, fair sharing, elasticity, and cross-cluster scheduling. Improve GPU utilization and cost efficiency through resource pooling and FinOps.
- Build lifecycle orchestration for online model serving, including model and image distribution, deployment, upgrades, rollback, autoscaling, multi-cluster operation, and disaster recovery.
- Build serving orchestration and traffic management capabilities for disaggregated serving clusters, including topology-aware scheduling, KV Cache affinity, intelligent request routing, and QoS/SLA management.
Requirements & Tech Stack
Minimum Qualifications
- Completing or recently completed a PhD's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field.
- Proficiency in at least one of Go, C++, or Python, with a solid foundation in data structures, algorithms, and software engineering principles.
- Familiarity with Linux and a foundational understanding of operating systems, computer networks, concurrent programming, and distributed systems.
- Strong hands-on and exploratory abilities, willingness to investigate systems through source code, metrics, logs, profiling, and experiments.
- A systematic and quantitative approach to problem-solving, ability to define measurements, test hypotheses, and validate system improvements.
- Demonstrated ownership and collaboration through coursework, research, internships, open-source contributions, or other engineering projects.
Preferred Qualifications
- Experience with Kubernetes, container runtimes, resource scheduling, quota management, multi-tenant systems, or FinOps.
- Contributions to open-source infrastructure projects such as Kubernetes, Volcano, Koordinator, or OpenKruise.
- Experience with model serving systems such as vLLM, SGLang, Triton, KServe, or Ray Serve, or an understanding of KV Cache, Continuous Batching, Prefill/Decode disaggregation, or model parallelism.
- Experience with online services, gateways, traffic management, autoscaling, performance optimization, or highly available distributed systems.
- Experience with GPU/NPU programming, heterogeneous resource scheduling, model distribution, or inference performance analysis.