AI/ML Professional
Summary
AI/ML Tech Lead who architects, builds, and scales multimodal AI systems (video, audio, image) for a media organization, leading teams on media understanding, personalization, search, content moderation, and automation. Core tech: CV/NLP/speech and multimodal transformers, distributed training (DeepSpeed, Horovod), and MLOps/inference tooling like MLflow, Ray, Airflow, KServe, and Triton.
Job Summary
The AI/ML Tech Lead will drive the end-to-end architecture, implementation, and scaling of multimodal AI systems within a media organization.
The role involves leading teams that deliver solutions across media understanding, personalization, search, content moderation, and automation, while ensuring engineering excellence, scalability, and robustness across AI systems.
Must-Have Skills
- Expert-level knowledge of Computer Vision (CV), NLP, Speech Models, and Multimodal Transformer Models
- Strong understanding of GPU optimization
- Hands-on experience with distributed training, including:
- DeepSpeed
- Horovod
- Experience with real-time near-real-time video processing
- Hands-on experience with:
- MLflow
- Ray
- Airflow
- KServe
- Triton Inference Server
- Vector Databases
- RAG
- LangChain
Preferred Skills
- Experience with Broadcast OTT platforms
- Experience with MAM (Media Asset Management) systems
- Experience with DAM (Digital Asset Management) workflows
- Experience with Generative Imaging, such as Stable Diffusion
- Experience with Video Generation
Qualifications
- 6 to 10 years of AI/ML experience, including leadership experience
- 5+ years of hands-on ML Engineering experience
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field
Key Responsibilities
Architecture & Technical Leadership
- Architect large-scale multimodal AI systems handling video, audio, and image pipelines.
- Design scalable training, inference, and data-ingestion systems for media AI applications.
- Lead the architecture and development of video AI capabilities, including:
- Scene Detection
- Video Summarization
- Content Moderation
- Annotation Workflows
- Multimodal Search & Discovery
- Design and optimize RAG pipelines using:
- Transcripts
- Video frames
- Subtitles
- Metadata
- Drive technical decisions around AI/ML architecture, scalability, performance, and reliability.
- Lead engineering teams in delivering production-ready AI solutions.
- Ensure AI systems are robust, scalable, and optimized for real-time or near-real-time media processing.
Key Screening Keywords
AI/ML Tech Lead | Machine Learning | Computer Vision | NLP | Speech Models | Multimodal AI | Transformers | GPU Optimization | DeepSpeed | Horovod | Real-Time Video Processing | MLflow | Ray | Airflow | KServe | Triton Inference Server | Vector DB | RAG | LangChain | Stable Diffusion | Video Generation | OTT | Broadcast | MAM | DAM