- Geylang Southeast (Singapore) Singapore
CLIPLY PTE. LTD. Hiring! Full Time Backend - Platform Engineer in Southeast (Singapore), Earn up to SGD 8,000 - Ricebowl
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Job Description
Responsibilities
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.
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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