AI ML tech lead

Honeybee Tech Solutions; United States; A distancia; USD 180.000 - 240.000; Jornada completa

Descripción de la vacante

Honeybee Tech Solutions is seeking an AI/ML Tech Lead to drive end-to-end architecture, implementation, and scaling of multimodal AI systems for media workflows. You will lead teams delivering media understanding, personalization, search, moderation, and automation.

The role requires hands-on expertise in CV, NLP, speech models, and multimodal transformers, with strong GPU optimization and distributed training. Manage cross-functional delivery and establish robust MLOps practices.

Formación

• 6–10 years AI/ML experience with leadership roles.
• 5+ years ML engineering experience.
• Bachelor's or Master's degree in CS/AI.

Responsabilidades

• Architect large-scale multimodal AI systems for video, audio, and image pipelines.
• Design scalable training, inference, and data ingestion for media AI.
• Lead design of video AI features: scene detection, video summarization, content moderation, annotation workflows, multimodal search.

Conocimientos

AI/ML leadership

Distributed training

MLOps

Cross-functional collaboration

Educación

Bachelor's/Master's in CS/AI

Herramientas

MLflow

Ray

Airflow

KServe

Triton Inference Server

Vector DBs

RAG

LangChain

Descripción del empleo

Role & responsibilities

Job Description

Must have: 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 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: MLflow, Ray, Airflow KServe, Triton Inference Server 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 6-10 years AI/ML experience, including leadership roles. 5+ years ML engineering experience. Bachelor's/Master's in CS/AI. 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.