The Role
Lead the architecture and scaling of multimodal AI pipelines that transform social media video, audio, captions, and metadata into structured data products. Build vision, speech, and language workflows; enforce validated extraction; fine-tune and serve open-source models; manage labeling and dataset quality; optimize inference costs; and establish technical roadmaps while mentoring developers.
Summary Generated by Built In
This is a remote position.
We are building a an AI & Data Lab focused on social media intelligence and influencer marketing data. We are seeking a Lead AI Systems Architect to design and scale our automated classification, enrichment, and multimodal AI pipelines. You will take raw, unstructured social content (short-form video, audio, captions, and visual metadata) and convert it into high-precision structured data products.
Responsibilities
- Design & Build Multimodal AI Pipelines: Combine Computer Vision (scene classification, aesthetic scoring), Speech-to-Text (Whisper), and LLMs into automated ingestion workflows.
- Structured Data Extraction: Implement programmatic extraction frameworks (Instructor, Pydantic, DSPy, Outlines) to enforce strict, validated JSON outputs from generative models.
- Model Optimization & Cost Control: Transition workloads from commercial APIs to fine-tuned open-source models (Llama 3/4, Qwen, DeepSeek) running on local inference engines (vLLM, TGI, Groq).
- Programmatic Labeling & Quality Control: Deploy data-centric AI frameworks (Cleanlab, Snorkel, Active Learning) to automate millions of labels and clean noisy datasets.
- Technical Leadership: Guide junior developers, establish engineering best practices, and set architectural roadmaps for data enrichment.
Requirements
- 5+ years of experience in Applied AI, Natural Language Processing, or Computer Vision.
- Proven experience building multimodal pipelines integrating vision, speech, and text models.
- Mastery of Python, PyTorch/TensorFlow, and production LLM orchestration tools (DSPy, Instructor, Pydantic, LangChain/LlamaIndex).
- Hands-on experience fine-tuning and serving open-source models using vLLM, TGI, or similar high-throughput inference engines.
- Experience with vector databases (Qdrant, pgvector, Pinecone) and RAG architectures at scale.
Preferred Qualifications
- Prior experience with social media data pipelines (TikTok, Instagram Reels, YouTube Shorts).
- Background in data-centric AI, active learning, or synthetic data generation.
Skills Required
- 5+ years of experience in Applied AI, Natural Language Processing, or Computer Vision
- Experience building multimodal pipelines integrating vision, speech, and text models
- Mastery of Python
- Mastery of PyTorch or TensorFlow
- Production experience with DSPy, Instructor, Pydantic, LangChain, or LlamaIndex
- Hands-on experience fine-tuning and serving open-source models using vLLM, TGI, or similar high-throughput inference engines
- Experience with vector databases such as Qdrant, pgvector, or Pinecone
- Experience with RAG architectures at scale
- Prior experience with social media data pipelines
- Background in data-centric AI, active learning, or synthetic data generation
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
AWISEE is a global digital marketing agency founded in 2018, specializing in SEO, Digital PR, and KOL and influencer marketing. It helps brands enter or expand in new markets through short-term visibility strategies and long-term growth solutions. Operating across Europe, North America, Asia, and the Middle East, the agency serves technology, SaaS, fintech, e-commerce, crypto, iGaming, and travel businesses worldwide.
