Machine Learning Systems Engineer

This is a fully remote position, open to applicants in Italy.

📋 Description

• Design, develop, and manage scalable backend services for a media intelligence platform, prioritizing clean, maintainable, and production-ready systems.

• Take ownership of essential backend components from system design and API specifications through to implementation, deployment, monitoring, and iterative improvements.

• Influence architectural choices across APIs, processing pipelines, distributed computing, storage solutions, search functionalities, observability, cloud infrastructure, and model-serving processes.

• Create data models and storage strategies for media assets, generated metadata, embeddings, processing tasks, model outputs, search indexes, and audit logs.

• Develop high-throughput media ingestion and processing pipelines capable of handling large quantities of video, audio, image, and text content.

• Construct distributed, event-driven workflows for media processing utilizing queues and pub/sub systems such as SQS, Kafka, Pub/Sub, or similar technologies.

• Implement reliable asynchronous processing methodologies, which include retries, idempotency, dead-letter queues, backpressure management, and fault-tolerant job execution.

• Lead the development and enhancement of workflows for metadata extraction, content analysis, scene detection, transcription, embedding generation, and multimodal AI inference.

• Collaborate with ML engineers, data scientists, and external model providers to benchmark models, assess quality/latency trade-offs, and safely implement model upgrades.

• Enhance AI/ML inference workflows for latency, throughput, reliability, and cost-effectiveness across both real-time and batch-processing scenarios.

• Deploy and manage systems on AWS, GCP, Azure, or other comparable cloud platforms, covering compute, storage, networking, queues, model-serving infrastructure, and monitoring systems.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field with equivalent practical experience.

• 5-7+ years of experience in backend engineering, specifically in building scalable distributed systems, media platforms, data pipelines, or high-throughput backend services.

• Previous experience managing significant backend modules end-to-end, encompassing architecture, implementation, deployment, monitoring, and production operations.

• Over 3 years of experience incorporating 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 in developing AI-driven processing pipelines for image, video, audio, or text analysis.

• Practical knowledge in optimizing production models, particularly for image, video, embedding, or multimodal models, including batching, caching, quantization, prompt optimization, routing strategies, latency reduction, and cost optimization.

• Prior familiarity with vector search, semantic search, media retrieval, or similarity-matching systems is highly preferred.

• Experience in mentoring engineers, leading technical discussions, and influencing architectural decisions across backend, infrastructure, and AI/ML workflows.

🏝️ Benefits

• Flexible work arrangements

• Professional development