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: 7 hours agoStatus: Live

Job Summary

Senior backend-focused ML engineer role building scalable media processing and AI-powered backend systems, with emphasis on data pipelines, vector search, and production-grade model integration across cloud platforms.

Location: Dublin

Workplace: Remote

Employment Type: Full time

Job Function: IT Operations (Systems/Network Admin)

Seniority: Manager level

Key Responsibilities

•Architect, build, and operate scalable backend services for a media intelligence platform, focusing on production-ready systems.
•Own critical backend components end to end, from design and API contracts through 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, metadata, embeddings, processing jobs, model outputs, search indexes, and audit trails.
•Design high-throughput 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.
•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 yearsDataAiMlBackendDistributed systems

Education:Bachelor's in Computer Science, Engineering

Languages:English

Tech Stack:PythonNode.jsHuggingFacePyTorchTensorFlowSQLNoSQLRESTAPIsAWSGCPAzureVector searchPineconeWeaviateQdrantElastic VectorsFAISS

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: 7 hours agoStatus: Live

Job Summary

Location: Dublin

Workplace: Remote

Employment Type: Full time

Job Function: IT Operations (Systems/Network Admin)

Seniority: Manager level

Key Responsibilities

•Architect, build, and operate scalable backend services for a media intelligence platform, focusing on production-ready systems.
•Own critical backend components end to end, from design and API contracts through 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, metadata, embeddings, processing jobs, model outputs, search indexes, and audit trails.
•Design high-throughput 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.
•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 yearsDataAiMlBackendDistributed systems

Education:Bachelor's in Computer Science, Engineering

Languages:English

Tech Stack:PythonNode.jsHuggingFacePyTorchTensorFlowSQLNoSQLRESTAPIsAWSGCPAzureVector searchPineconeWeaviateQdrantElastic VectorsFAISS

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