Machine Learning Systems Engineer

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

📋 Description

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

• Take ownership of essential backend components from start to finish, encompassing system design, API contracts, implementation, deployment, monitoring, and iterative enhancements.

• Influence architectural choices related to APIs, processing pipelines, distributed computing, storage solutions, search capabilities, observability, cloud infrastructure, and model-serving workflows.

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

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

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

• Implement robust asynchronous processing patterns, including retries, idempotency, dead-letter queues, backpressure management, and fault-tolerant job execution.

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

• Integrate and optimize AI/ML services within backend workflows, covering model APIs, embedding pipelines, OCR, speech-to-text, scene analysis, multimodal inference, batching, caching, and fallback strategies.

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

• Observe model and system performance in production, including API latency, queue depth, processing duration, model error rates, GPU utilization, confidence distributions, drift signals, and cost per processed item.

⛳️ Requirements

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.

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

• Prior experience managing significant backend modules from inception to deployment, including architecture, implementation, monitoring, and production operations.

• At least 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.

• Practical experience in creating AI-driven processing pipelines for image, video, audio, or text analysis.

• Hands-on knowledge in optimizing production models, particularly for image, video, embedding, or multimodal models, encompassing batching, caching, quantization, prompt optimization, routing strategies, latency reduction, and cost efficiency.

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

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

🏝️ Benefits

• Flexible working hours

• Professional development opportunities