Bringing real world currency to the blockchain.
Machine Learning Systems Engineer
Location
Romania
Posted
2 days ago
Salary
0
Seniority
Senior
Job Description
Machine Learning Systems Engineer
Tether.to
• 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. • Build distributed, event-driven workflows for media processing using queues and pub/sub systems such as SQS, Kafka, Pub/Sub, or equivalent technologies. • Implement reliable asynchronous processing patterns, including retries, idempotency, dead-letter queues, backpressure handling, and fault-tolerant job execution. • Lead the development and optimization of metadata extraction, content analysis, scene detection, transcription, embedding generation, and multimodal AI inference workflows.
Job 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.
- Practical experience with production model optimization, especially for image, video, embedding, or multimodal models, including batching, caching, quantization, prompt optimization, routing strategies, latency reduction, and cost optimization.
- Prior experience with vector search, semantic search, media retrieval, or similarity-matching systems is strongly preferred.
- Experience mentoring engineers, leading technical discussions, and influencing architectural decisions across backend, infrastructure, and AI/ML workflows.
Benefits
- Flexible working arrangements
- Professional development opportunities
- Collaborative global team
- Access to cutting-edge technologies
- Opportunities for career advancement
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