AI/ML Professional

Honeybee Tech Solutions; Hyderabad, Pune District, Bengaluru; Sur place; INR 400 000 - 700 000; Plein temps

Résumé du poste

Honeybee Tech Solutions is hiring an AI/ML Tech Lead to drive end-to-end architecture, implementation, and scaling of multimodal AI systems within a media organization. You will lead teams delivering solutions across media understanding, personalization, search, content moderation, and automation, ensuring engineering excellence, scalability, and robustness.

The role covers architecture, real-time video processing, and building scalable training/inference pipelines, including RAG, transcripts,

Qualifications

• Expert-level knowledge of CV, NLP, speech models and multimodal transformers.
• Strong understanding of GPU optimization and scalable training.
• Hands-on experience with distributed training tools (DeepSpeed, Horovod).
• Experience with real-time near-real-time video processing and AI pipelines.
• Hands-on experience with MLflow, Ray, Airflow, KServe, Triton, vector databases, RAG, LangChain.

Responsabilités

• Architect large-scale multimodal AI systems for video, audio, and image pipelines.
• Design scalable training, inference, and data ingestion for media AI apps.
• Lead architecture and development of video AI capabilities: scene detection, summarization, content moderation, annotation workflows, and multimodal search.
• Design and optimize RAG pipelines using transcripts, video frames, subtitles and metadata.
• Drive decisions on AI/ML architecture, scalability, performance, reliability.
• Lead engineering teams to deliver production-ready AI solutions.
• Ensure AI systems are robust and optimized for real-time or near-real-time media processing.

Connaissances

Computer Vision

NLP

Speech Models

Multimodal Transformers

GPU Optimization

Distributed Training

Real-Time Video Processing

Video AI

RAG

LangChain

Stable Diffusion

Formation

Bachelor's or Master's in Computer Science, Artificial Intelligence, or related field

Outils

DeepSpeed

Horovod

MLflow

Ray

Airflow

KServe

Triton Inference Server

Vector Databases

RAG

LangChain

Description du poste

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