AI Engineer - Classifiers, Media Intelligence & Voice R&D
这是一个远程职位。我们的客户正在寻找一个创新和驱动的 AI 工程师加入他们的团队。作为媒体智能和人工智能驱动内容创造领域的领导者，他们最近扩大了他们的 AI 语音和图像技术工作，推动下一代尖端产品的发展。这个角色将集中在创造，分类和组织大量人工智能生成的媒体，以及引领人工智能声音和音频生成和高级图像智能能力的研发。工作描述责任：· 设计，训练和部署内容管道的分类模型，包括生成媒体的风格检测，质量评分，内容调节，过和语义分类。· 为媒体图书馆开发和维护自动标签和组织系统：提取属性，检测视觉功能，集群类似内容并实现智能搜索。· 构建和优化培训数据管道：创建注释工具，策划数据集，建立活跃学习循环，确保高品质标记数据。· 领导人工智能声音和音频生成的研发，包括语音克隆，文字到语言以及音频合成；· 研究和原型图像智能技术，如面部/身体分析，姿势估计，风格转移以及图像与图像一致性。· 开发评估框架来测量分类器的准确性，生成模型的质量和模型漂移随时间而推移。·优化性能，成本和延迟的推断管道集成批量处理，定量化，缓存和模型服务策略。· 与 GPU 计算基础设施整合并通过生产 API 提供模型。要求 · 3年以上生产和部署机器学习模型的经验，特别是分类，标签或内容理解。·实践训练，包括数据集策划，与架构进行实验，调整超参数和调试。· 强大的背景图像分类和计算机视觉技术 （例如 CNN,视觉转换器，CLIP）. · 对语音/音频人工智能 （如文字到语言，语音克隆，音频分类）的经验或证明兴趣。· Python 熟练，有 PyTorch 或 TensorFlow 的经验。·
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This is a remote position.
Our client is looking for an innovative and driven AI Engineer to join their team. A leader in media intelligence and AI-driven content creation, they have recently expanded their work in AI voice and image technologies, driving the development of the next generation of cutting-edge products. This role will focus on the creation, classification, and organization of massive volumes of AI-generated media, along with spearheading R&D into AI voice and audio generation and advanced image intelligence capabilities.
Job Description
Responsibilities:
- 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.
Requirements
- 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.
Qualifications:
- 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.
Benefits
- 100% remote, full-time role.
- Flexible work hours.
- Competitive salary and comprehensive benefits package.
- Opportunity for career advancement and personal development.
- Work on high-impact projects with cutting-edge AI technologies.
Originally posted on Himalayas