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Urgent! Coding Limits - AI/ML Architect - LLM/Computer Vision Vacancy | CODINGLIMITS PRIVATE LIMITED
<p><p><b>Description :</b><br/><br/>Job Title : AI/ML Architect<br/><br/>Experience : 10+ years<br/><br/>Industry : Media (Preferred)<br/><br/><b>Role Summary :</b><br/><br/>The AI/ML Architect defines the enterprise AI strategy and leads the architecture for multimodal AI across the organization.
This role focuses on building advanced capabilities in media understanding, LLM workflows, multimodal RAG, real-time metadata enrichment, content intelligence, personalization, and the scalable AI platform infrastructure required to support them.<br/><br/>You will guide the technical vision for AI across teams, ensuring the media organization leverages state-of-the-art multimodal, generative, and agentic AI technologies.<br/><br/><b>Detailed Responsibilities :</b><br/><br/><b>Enterprise Architecture & Strategy :</b><br/><br/>Define and maintain the long-term AI architecture roadmap across :<br/><br/>- NLP, computer vision, ASR, and video AI<br/><br/>- Multimodal LLMs (textimageaudiovideo)<br/><br/>- Recommendation systems and personalization<br/><br/>- Content moderation and compliance automation<br/><br/>- Retrieval-Augmented Generation (RAG) and enterprise knowledge systems<br/><br/>- Agentic/automation-driven AI systems<br/><br/>- Architect scalable media ingestion and processing pipelines capable of handling 10,000+ hours of video content.<br/><br/>- Establish standards for model lifecycle management, governance, auditability, lineage, and reproducibility.<br/><br/><b>Platform & Infrastructure :</b><br/><br/>- Architect and optimize GPU clusters, distributed compute, HPC workloads, and cloud-native AI platforms.<br/><br/>Lead integration across core media and data systems, including :<br/><br/>- Media Asset Management (MAM) platforms<br/><br/>- Content Management Systems (CMS)<br/><br/>- Data lakes/lakehouses<br/><br/>- Vector databases and similarity search systems<br/><br/>- Observability, monitoring, and performance telemetry tools<br/><br/>- Define and enforce best practices for MLOps and LLMOps tooling, CI/CD pipelines, evaluation frameworks, and automated deployment.<br/><br/><b>Governance & Compliance :</b><br/><br/>Ensure adherence to :<br/><br/>- Content safety and trust guidelines<br/><br/>- Copyright, IP protection, and digital rights management<br/><br/>- Global data privacy regulations (GDPR, CCPA, etc.)<br/><br/>- Responsible AI standards, including NIST AI RMF<br/><br/>- Implement guardrails, policy enforcement, and human-in-the-loop processes for safe AI operations.<br/><br/><b>Innovation & Leadership :</b><br/><br/>- Evaluate emerging technologies in multimodal and generative AI, including video generation, audio synthesis, and agentic systems.<br/><br/>- Drive adoption of new frameworks, LLMOps patterns, and reusable AI platform components.<br/><br/>- Partner with cross-functional leaders and present architectural strategies to VP and C-level stakeholders.<br/><br/>- Mentor engineering teams, support the creation of an AI Center of Excellence (AI COE), and set organization-wide AI best practices.<br/><br/><b>Must-Have Skills :</b><br/><br/>- Deep expertise in multimodal AI (text, image, audio, video).<br/><br/>- Strong mastery of LLMs, fine-tuning frameworks, adapters/LoRA, and vector search.<br/><br/>- Expert-level experience with cloud architecture (Azure, AWS, or GCP).<br/><br/>- Proven ability to design and operate enterprise-scale MLOps + LLMOps systems.<br/><br/>- Strong background in high-scale media processing and distributed pipelines.<br/><br/><b>Preferred Skills :</b><br/><br/>- Experience with generative video, audio synthesis, diffusion models, or generative media pipelines.<br/><br/>- Experience building AI platforms, AI Centers of Excellence, or internal AI acceleration teams.<br/><br/>- Background in recommendation engines, personalization, or real-time content intelligence.<br/><br/><b>Qualifications :</b><br/><br/>- 10+ years in AI/ML engineering, research, or architecture roles.<br/><br/>- 3+ years architecting enterprise-scale AI/ML or data/compute platforms.<br/><br/>- Masters or Ph.D. in Computer Science, Machine Learning, or a related field (preferred).</p><br/></p> (ref:hirist.tech)
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