Staff ML Systems Engineer - Media Intelligence

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Architect, build, and operate scalable backend services for a media intelligence platform, owning critical backend components end to end—from API design to deployment and monitoring. Drive decisions across APIs, processing pipelines, and model-serving; design data models for media assets and metadata; create high-throughput ingestion and processing pipelines; build event-driven workflows using SQS/Kafka/Pub/Sub for reliable, scalable AI-powered media analysis.

Location: Copenhagen

Workplace: Remote

Employment Type: Full time

Job Function: IT Operations (Systems/Network Admin)

Key Responsibilities

•Architect, build, and operate scalable backend services for a media intelligence platform, with a focus on clean, maintainable, and production-ready systems.
•Own critical backend components end to end, from system design and API contracts through implementation, deployment, monitoring, and iteration.
•Drive architectural decisions across APIs, processing pipelines, distributed compute, storage, search, observability, cloud infrastructure, and model-serving workflows.
•Design data models and storage patterns for media assets, generated metadata, embeddings, processing jobs, model outputs, search indexes, and audit trails.
•Design high-throughput media ingestion and processing pipelines for large volumes of video, audio, image, and text content.

Key Requirements

•Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
•5-7+ years of backend engineering experience, ideally building scalable distributed systems, media platforms, data pipelines, or high-throughput backend services.
•Prior experience owning major backend modules end to end, including architecture, implementation, deployment, monitoring, and production operations.
•3+ years of experience integrating AI/ML inference systems into backend workflows, including model APIs, embedding pipelines, OCR, speech-to-text, scene detection, or multimodal model outputs.
•Hands-on experience creating AI-powered processing pipelines for image, video, audio, or text analysis.

Experience:5-7 yearsAIMLMediaCloudBackendDistributed systemsData pipelines

Education:Bachelor's

Skills:LeadershipMentoringCollaborationProblem-solving

Languages:English

Tech Stack:PythonNode.jsHuggingFacePyTorchTensorFlowSQLNoSQLSQSPub/SubKafkaAWSGCPAzureVLLMTritonSageMakerVertex AIPineconeWeaviateQdrant

Company Brief

Tether.io

Builds tools and services to help companies hire, onboard, and manage remote or distributed teams across borders, focusing on payroll, compliance, and global employment workflows.

Industry: HR Tech

Website

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Tether.io

1 month ago

Staff ML Systems Engineer - Media Intelligence

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Location: Copenhagen

Workplace: Remote

Employment Type: Full time

Job Function: IT Operations (Systems/Network Admin)

Key Responsibilities

•Architect, build, and operate scalable backend services for a media intelligence platform, with a focus on clean, maintainable, and production-ready systems.
•Own critical backend components end to end, from system design and API contracts through implementation, deployment, monitoring, and iteration.
•Drive architectural decisions across APIs, processing pipelines, distributed compute, storage, search, observability, cloud infrastructure, and model-serving workflows.
•Design data models and storage patterns for media assets, generated metadata, embeddings, processing jobs, model outputs, search indexes, and audit trails.
•Design high-throughput media ingestion and processing pipelines for large volumes of video, audio, image, and text content.

Key Requirements

•Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
•5-7+ years of backend engineering experience, ideally building scalable distributed systems, media platforms, data pipelines, or high-throughput backend services.
•Prior experience owning major backend modules end to end, including architecture, implementation, deployment, monitoring, and production operations.
•3+ years of experience integrating AI/ML inference systems into backend workflows, including model APIs, embedding pipelines, OCR, speech-to-text, scene detection, or multimodal model outputs.
•Hands-on experience creating AI-powered processing pipelines for image, video, audio, or text analysis.

Experience:5-7 yearsAIMLMediaCloudBackendDistributed systemsData pipelines

Education:Bachelor's

Skills:LeadershipMentoringCollaborationProblem-solving

Languages:English

Tech Stack:PythonNode.jsHuggingFacePyTorchTensorFlowSQLNoSQLSQSPub/SubKafkaAWSGCPAzureVLLMTritonSageMakerVertex AIPineconeWeaviateQdrant

Company Brief

Tether.io

Builds tools and services to help companies hire, onboard, and manage remote or distributed teams across borders, focusing on payroll, compliance, and global employment workflows.

Industry: HR Tech

Website