Machine Learning Systems Engineer

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

📋 Description

• Design, construct, and maintain scalable backend services for a media intelligence platform, emphasizing clean, maintainable, and production-ready systems.

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

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

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

• 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.

• Apply reliable asynchronous processing techniques, including retries, idempotency, dead-letter queues, backpressure management, and fault-tolerant job execution.

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

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

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

⛳️ Requirements

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

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

• Previous 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 developing AI-powered processing pipelines for image, video, audio, or text analysis.

• Experience with production model optimization, particularly for image, video, embedding, or multimodal models, focusing on batching, caching, quantization, prompt optimization, routing strategies, latency reduction, and cost management.

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

• Proven track record of mentoring engineers, facilitating technical discussions, and shaping architectural decisions within backend, infrastructure, and AI/ML workflows.

🏝️ Benefits

• Flexible working hours

• Professional development opportunities