2 дня назад
Platform Engineer (AI/ML)
150 000 - 250 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Platform Engineer (AI/ML): Building and operating scalable AWS infrastructure and backend platform systems for an AI/ML platform with an accent on reliability, deployment safety, cost efficiency, and developer experience. Focus on designing autoscaling and high-concurrency systems, automating CI/CD and observability, and managing incident response for production services.
Location: On-site in Singapore, with on-site consideration in San Francisco; fully remote arrangements are available for candidates based in Europe or other regions outside the US and Southeast Asia.
Salary: $150,000–$250,000 USD annually
Company
operates an AI/ML platform requiring reliable, scalable infrastructure and developer tooling.
What you will do
- Own uptime, latency, provisioning speed, infrastructure cost, and incident response for core platform services.
- Build and maintain AWS infrastructure with Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management.
- Design backend and platform systems for capacity planning, autoscaling, queueing, backpressure, retries, cleanup, and rollback workflows.
- Develop dashboards, alerts, logs, traces, SLOs, runbooks, and on-call processes.
- Build CI/CD pipelines, release automation, environment management, and deployment workflows.
- Automate systems, improve backend services, and create internal developer tooling.
Requirements
- 2–4 years of experience owning production cloud infrastructure for a high-availability, user-facing platform.
- Hands-on experience with AWS and containerized systems, including Terraform, Kubernetes/EKS, Docker, EC2, networking, load balancers, and secrets management.
- Experience with CI/CD, release automation, observability, alerting, and incident response.
- Strong backend engineering judgment across service architecture, APIs, databases, asynchronous systems, queues, and production failure modes.
- Experience designing systems for bursty workloads, long-running jobs, sandboxed execution, distributed workers, or high-concurrency services.
- Prior AI/ML platform or AI/ML software engineering experience; experience reducing cloud spend through architecture, autoscaling, workload placement, caching, or cleanup systems.
Nice to have
- Experience operating infrastructure for data-heavy, ML/AI, workflow, marketplace, developer-tools, or enterprise platforms.
Culture & Benefits
- Work on a tight-knit engineering team of approximately 15 people.
- Visa sponsorship is available.
- On-site and region-specific remote work arrangements are available.
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