AI/ML Professional

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**