Description
AI/ML Engineer- Tech Lead
Job Title : AI/ML Engineer Tech Lead Level
Experience : 710 years
Industry : Media Preferred
Role Summary
- The AI/ML Tech Lead drives the end-to-end architecture, implementation, and scaling of multimodal AI systems in the media organization.
- They lead teams delivering media understanding, personalization, search, moderation, and automation.
- This role ensures engineering excellence, scalability, and robustness in all AI systems.
Detailed 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.
- Lead design of video AI features such as :
- Scene detection
- Video summarization
- Content moderation
- Annotation workflows
- Multimodal search and discovery
- Design and optimize RAG pipelines pulling from transcripts, frames, subtitles, metadata.
Execution & Delivery
- Oversee model development, integration, deployment, and monitoring.
- Manage cross-functional delivery with engineers, designers, and media teams.
- Drive sprint planning, architecture reviews, and performance evaluations.
Technical Excellence & Governance
- Enforce best practices in coding, testing, model governance, and documentation.
- Build and maintain MLOps standards and model lifecycle processes.
- Ensure secure, compliant handling of media assets and user data.
Team Leadership
- Mentor ML engineers across levels.
- Lead technical interviews, onboarding, and capability building.
Must-Have Skills
- Expert in CV, NLP, speech models, and multimodal transformer models.
- Strong understanding of GPU optimization, distributed training (DeepSpeed, Horovod).
- Experience with real-time/near-real-time video processing.
- Hands-on with :
i. MLflow, Ray, Airflow
ii. KServe, Triton Inference Server
iii. Vector DBs, RAG, LangChain
Preferred Skills
- Experience with broadcast/OTT platforms, MAM systems, and DAM workflows.
- Experience with generative imaging (Stable Diffusion) or video generation.
Qualifications
- 7 to 10 years AI/ML experience, including leadership roles.
- 5 years+ ML engineering experience.
- Bachelors/Masters in CS/AI
(ref:hirist.tech)
