ByteDance

1 day ago

Production Engineer - Applied Machine Learning Engine (Singapore)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Build and run high-availability machine learning training, inference, and storage systems for ByteDance’s Data-AML team. Own production operations, including scheduling/orchestration, Kubernetes and GPU cluster operations, distributed training, and Parameter Server/NoSQL storage. Establish SLO/SLA frameworks, observability, alerting, on-call, incident response, and disaster recovery. Improve delivery with CI/CD, canary deployments, automated rollback, health checks, and elastic scaling, while optimizing GPU/CPU/storage/network resources.

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Own production operations management and stability assurance for AML training, inference, and storage systems, including scheduling/orchestration, Kubernetes/GPU clusters, distributed training, online inference serving, and Parameter Server/NoSQL storage.
•Build and maintain SLO/SLA frameworks, observability, alerting, on-call processes, incident diagnosis, self-healing, disaster recovery, and post-incident review (postmortem) practices.
•Drive engineering capabilities such as CI/CD, canary/gradual deployments, automated rollback, system health inspections, pre-flight checks, capacity forecasting, and elastic scaling.
•Lead resource governance and optimization across GPU, CPU, storage, and network infrastructure, including quota management, cost attribution, and performance tuning.
•Collaborate across teams to resolve complex technical challenges impacting availability and system performance.

Key Requirements

•Bachelor’s degree or above in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
•Proficient in Linux and skilled in at least one: Shell, Python, Go, or C++.
•Familiar with ML training/inference architectures, Kubernetes, GPU clusters, or distributed storage systems.
•Experienced in production issue troubleshooting, performance analysis, and automation platform development.
•Strong ownership and analytical/problem-solving skills with ability to drive cross-functional collaboration to resolve complex technical issues.

Experience:Machine learningDistributed systemsKubernetesGPUNoSQLFinOpsOpen source infrastructure

Education:Bachelor's in Computer Science, Software Engineering, Artificial Intelligence, or a related field

Skills:OwnershipAnalytical skillsProblem-solvingCross-functional collaborationIncident troubleshooting

Tech Stack:LinuxShellPythonGoC++KubernetesK8sGPU clustersCI/CDCanary deploymentsDistributed trainingOnline inference servingParameter ServerNoSQLKV CachesMooncakeObservabilityAlertingPostmortemDisaster recovery

Company Brief

ByteDance

Develops consumer internet and content platforms, including TikTok and other apps for short-form video, news, and entertainment. It also builds advertising, commerce, and creator tools that connect audiences, brands, and publishers across global markets.

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Headquarters: Beijing, China

Founded: 2012

Website LinkedIn

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ByteDance

1 day ago

Production Engineer - Applied Machine Learning Engine (Singapore)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Own production operations management and stability assurance for AML training, inference, and storage systems, including scheduling/orchestration, Kubernetes/GPU clusters, distributed training, online inference serving, and Parameter Server/NoSQL storage.
•Build and maintain SLO/SLA frameworks, observability, alerting, on-call processes, incident diagnosis, self-healing, disaster recovery, and post-incident review (postmortem) practices.
•Drive engineering capabilities such as CI/CD, canary/gradual deployments, automated rollback, system health inspections, pre-flight checks, capacity forecasting, and elastic scaling.
•Lead resource governance and optimization across GPU, CPU, storage, and network infrastructure, including quota management, cost attribution, and performance tuning.
•Collaborate across teams to resolve complex technical challenges impacting availability and system performance.

Key Requirements

•Bachelor’s degree or above in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
•Proficient in Linux and skilled in at least one: Shell, Python, Go, or C++.
•Familiar with ML training/inference architectures, Kubernetes, GPU clusters, or distributed storage systems.
•Experienced in production issue troubleshooting, performance analysis, and automation platform development.
•Strong ownership and analytical/problem-solving skills with ability to drive cross-functional collaboration to resolve complex technical issues.

Experience:Machine learningDistributed systemsKubernetesGPUNoSQLFinOpsOpen source infrastructure

Education:Bachelor's in Computer Science, Software Engineering, Artificial Intelligence, or a related field

Skills:OwnershipAnalytical skillsProblem-solvingCross-functional collaborationIncident troubleshooting

Company Brief

ByteDance

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Headquarters: Beijing, China

Founded: 2012

Website LinkedIn