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 and build scalable backend services for a media intelligence platform, integrating AI/ML workflows, vector search, and multimodal analysis. Lead end-to-end backend components, data models, and model-serving pipelines, ensuring low-latency processing of video, audio, image, and text content across cloud platforms.

Location: Bengaluru

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.
•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.
•Practical experience with production model optimization, including batching, caching, quantization, prompt optimization, routing strategies, latency reduction, and cost optimization.

Experience:5-7 yearsAI/MLBackendDistributed systemsMedia processing

Education:Bachelor's

Skills:PythonNode.jsPyTorchTensorFlowSQLNoSQLRESTAPIsData modelingScaling

Languages:English

Tech Stack:PythonNode.jsPyTorchTensorFlowSQLNoSQLSQSKafkaPub/SubAWSGCPAzureRESTAPIVector searchPineconeWeaviateQdrantFAISS

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: Bengaluru

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.
•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.
•Practical experience with production model optimization, including batching, caching, quantization, prompt optimization, routing strategies, latency reduction, and cost optimization.

Experience:5-7 yearsAI/MLBackendDistributed systemsMedia processing

Education:Bachelor's

Skills:PythonNode.jsPyTorchTensorFlowSQLNoSQLRESTAPIsData modelingScaling

Languages:English

Tech Stack:PythonNode.jsPyTorchTensorFlowSQLNoSQLSQSKafkaPub/SubAWSGCPAzureRESTAPIVector searchPineconeWeaviateQdrantFAISS

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