<p><p><b>Description :</b> AI/ML Engineer- Tech Lead <br/><br/><b>Job Title :</b> AI/ML Engineer Tech Lead Level <br/><br/><b>Experience :</b> 7 to 10 years <br/><br/><b>Industry :</b> Media Preferred <br/><br/><b>Role Summary</b> <br/><br/>The AI/ML Tech Lead drives the end-to-end architecture, implementation, and scaling of multimodal AI systems in the media organization.
</p><p><br/></p><p>They lead teams delivering media understanding, personalization, search, moderation, and automation.
This role ensures engineering excellence, scalability, and robustness in all AI systems.
<br/><br/><b>Detailed Responsibilities :</b><br/><br/><b>Architecture & Technical Leadership :</b><br/><br/>- Architect large-scale multimodal AI systems handling video, audio, and image pipelines.
<br/><br/>- Design scalable training, inference, and data ingestion systems for media AI.
<br/><br/>Lead design of video AI features such as : <br/><br/>- Scene detection <br/><br/>- Video summarization <br/><br/>- Content moderation <br/><br/>- Annotation workflows <br/><br/>- Multimodal search and discovery <br/><br/>- Design and optimize RAG pipelines pulling from transcripts, frames, subtitles, metadata.
<br/><br/><b>Execution & Delivery</b> <br/><br/>- Oversee model development, integration, deployment, and monitoring.
<br/><br/>- Manage cross-functional delivery with engineers, designers, and media teams.
<br/><br/>- Drive sprint planning, architecture reviews, and performance evaluations.
<br/><br/><b>Technical Excellence & Governance</b> <br/><br/>- Enforce best practices in coding, testing, model governance, and documentation.
<br/><br/>- Build and maintain MLOps standards and model lifecycle processes.
<br/><br/>- Ensure secure, compliant handling of media assets and user data.
<br/><br/><b>Team Leadership</b> <br/><br/>- Mentor ML engineers across levels.
<br/><br/>- Lead technical interviews, onboarding, and capability building.
<br/><br/><b>Must-Have Skills</b> <br/><br/>- Expert in CV, NLP, speech models, and multimodal transformer models.
<br/><br/>- Strong understanding of GPU optimization, distributed training (DeepSpeed, Horovod).
<br/><br/>- Experience with real-time/near-real-time video processing.
<br/><br/>- Hands-on with : <br/><br/>- MLflow, Ray, Airflow <br/><br/>- KServe, Triton Inference Server <br/><br/>- Vector DBs, RAG, LangChain <br/><br/><b>Preferred Skills</b> <br/><br/>- Experience with broadcast/OTT platforms, MAM systems, and DAM workflows.
<br/><br/>- Experience with generative imaging (Stable Diffusion) or video generation.
<br/><br/><b>Qualifications</b> <br/><br/>- 7 to 10 years AI/ML experience, including leadership roles.
<br/><br/>- 5 years+ ML engineering experience.
<br/><br/>- Bachelors/Masters in CS/AI.
</p><br/></p> (ref:hirist.tech)