WOW Remote Teams

AI Engineer- Classifiers, Media Intelligence & Voice R&D

Rol remoto de AI Engineering con fit claro de ubicación del candidato.

Publicado23 jul 2026

Países elegibles1 país aceptado

Señal de senioritySenior

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

Estados Unidos

Resumen del rol

Contenido del rol extraído en secciones para revisar más rápido.

Design, train, and deploy classification models for content pipeline, including style detection, quality scoring, content moderation, filtering, and semantic categorization of generated media.
Develop and maintain automated tagging and organization systems for the media library: extracting attributes, detecting visual features, clustering similar content, and enabling intelligent search.
Build and optimize training data pipelines: create annotation tooling, curate datasets, establish active learning loops, and ensure high-quality labeled data.
Lead R&D into AI voice and audio generation, including voice cloning, text-to-speech, and audio synthesis; prototype integrations and create a production-ready pathway from research to features.
Research and prototype image intelligence technologies such as face/body analysis, pose estimation, style transfer, and image-to-image consistency.
Develop evaluation frameworks to measure the accuracy of classifiers, the quality of generation models, and model drift over time.
Optimize inference pipelines for performance, cost, and latency—incorporating batching, quantization, caching, and model serving strategies.
Integrate with GPU compute infrastructure and deliver models via production APIs.

3+ years of experience building and deploying machine learning models in production, particularly in classification, tagging, or content understanding.
Hands-on experience with model training, including dataset curation, experimenting with architectures, tuning hyperparameters, and debugging.
Strong background in image classification and computer vision techniques (e.g., CNNs, vision transformers, CLIP).
Experience or demonstrated interest in voice/audio AI (e.g., text-to-speech, voice cloning, audio classification).
Proficiency in Python, with experience in PyTorch or TensorFlow.
Experience with building data labeling pipelines, annotation workflows, or active learning systems.
Understanding of model serving in production environments, including REST APIs and latency optimization.

Bachelor’s degree or higher in Computer Science, Engineering, or related field.
Experience in AI/ML, particularly in content classification, tagging, and media organization systems.
Proven experience with Python and ML frameworks like PyTorch or TensorFlow.
Strong communication skills to collaborate with R&D teams and integrate new technologies into production.

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