jobs in CLIPLY PTE. LTD.

全职 Backend - Platform Engineer 工作, 薪水 up to SGD 5,000, CLIPLY PTE. LTD. Central Region (Singapore) 公司招聘中 - Ricebowl

Backend - Platform Engineer

CLIPLY PTE. LTD.

Central Region (Singapore)

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工作地点

  • 61 UBI ROAD 1 Central Region (Singapore) Singapore

职位描述

岗位职责

Role Overview
Cliply is building a high-throughput, multimodal AI platform that processeslong-form video, audio, and text to generate structured narrative intelligencefor broadcasters and media companies. As a Backend / Platform Engineer, youwill design and operate the distributed systems, media pipelines and model‑servinginfrastructure that power Cliply’s core engine.

You will work closely with AI/MLengineers to integrate perception models, multimodal alignment models andLLM/VLM inference services into a scalable production environment. This role iscritical to transforming our AI engine into a reliable, production‑readyplatform.

Key Responsibilities

Media & AI PipelineEngineering

  • Build ingestion pipelines for long‑form video, audio and transcripts (multi‑hour content).
  • Design distributed processing workflows for frame extraction, audio segmentation and metadata generation.
  • Implement asynchronous job orchestration for long‑running tasks (video processing, multimodal alignment, inference batching).
  • Integrate GPU‑backed model‑serving endpoints (LLMs, VLMs, perception models) via REST/gRPC.
  • Build caching, batching and scheduling layers for high‑volume inference workloads.

Backend Architecture &Microservices

  • Design and implement REST/gRPC APIs for content ingestion, retrieval, metadata access and response‑tree execution.
  • Build microservices that orchestrate multimodal pipelines, queues and background workers.
  • Implement robust retry logic, backpressure handling and distributed task management.
  • Develop scalable storage layers for embeddings, metadata graphs, timelines and multimodal outputs.

Cloud Infrastructure &Deployment

  • Architect and operate cloud environments (AWS/GCP) for development, staging and production.
  • Deploy containerised services using Kubernetes (EKS/GKE) for microservices and model serving.
  • Implement CI/CD pipelines for backend and ML components, including automated tests and blue‑green deployments.
  • Manage object storage (S3/GCS) for large media assets and multimodal datasets.

Observability, Reliability& Security

  • Implement monitoring, logging and tracing for long‑running pipelines and inference services.
  • Build dashboards for pipeline health, throughput, latency and failure analysis.
  • Ensure security best practices across authentication, authorisation, rate limiting and usage tracking.
  • Conduct performance tuning for high‑throughput, low‑latency workloads.

Collaboration & SystemDesign

  • Work closely with AI/ML engineers to integrate perception and multimodal models into backend workflows.
  • Collaborate with frontend engineers to expose APIs and support creative‑workflow features.
  • Participate in architecture reviews, design discussions and technical roadmap planning.

Requirements

Must‑Have

  • 4–7+ years of experience in backend, platform or distributed systems engineering.
  • Strong proficiency in Python, Go, Java or Node.js/TypeScript.
  • Experience with microservices, REST/gRPC APIs and asynchronous processing.
  • Hands‑on experience with distributed queues (Kafka, RabbitMQ, SQS, Pub/Sub).
  • Experience deploying services on AWS or GCP (EKS/GKE, EC2/Compute Engine, S3/GCS).
  • Strong understanding of scalability, reliability, concurrency and fault‑tolerance.
  • Experience with Docker, Kubernetes and CI/CD pipelines.
  • Familiarity with large object storage and high‑volume data pipelines.

Nice‑to‑Have

  • Experience integrating ML model‑serving frameworks (Triton, TorchServe, custom gRPC).
  • Experience with GPU scheduling, inference batching or multimodal pipelines.
  • Experience with media processing (FFmpeg, video/audio extraction, streaming APIs).
  • Experience with observability stacks (Prometheus, Grafana, OpenTelemetry).
  • Cloud certifications (AWS/GCP) or prior experience with high‑throughput systems.

Why Cliply

  • Build the core engine of a next‑generation multimodal AI platform for the media industry.
  • Work directly with senior AI engineers on perception, multimodal alignment and long‑form reasoning.
  • Solve complex distributed‑systems challenges at the intersection of media, AI and cloud infrastructure.
  • Join a pre‑seed team where your work directly shapes the product, architecture and future of the company.

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