Lead AI Systems Architect (Data-Centric AI & Multimodal)

About the role

We are seeking a Lead AI Systems Architect to design and scale advanced AI systems that convert unstructured social media content into high‑quality structured data products. This senior role combines applied AI, data engineering, and multimodal pipeline development.

Key responsibilities

• Design and build automated multimodal ingestion pipelines integrating computer vision, speech‑to‑text (e.g., Whisper), and large language models.
• Develop frameworks for structured data extraction using tools such as Instructor, Pydantic, DSPy, and Outlines.
• Transition workloads from commercial APIs to fine‑tuned open‑source models (Llama, Qwen, DeepSeek) deployed via vLLM, TGI, or similar inference engines.
• Implement data‑centric AI techniques (Cleanlab, Snorkel, active learning) for large‑scale labeling and dataset quality improvement.
• Define architectural roadmaps, set engineering standards, and mentor junior developers.

Required profile

• At least 5 years of applied AI experience, including NLP and computer vision.
• Proven track record building multimodal pipelines that combine vision, speech, and text models.
• Strong Python programming skills and deep‑learning expertise with PyTorch or TensorFlow.

Required skills

• Python
• PyTorch or TensorFlow
• DSPy, Instructor, Pydantic, LangChain, LlamaIndex
• vLLM, TGI (or comparable high‑throughput inference engines)
• Vector databases such as Qdrant, pgvector, Pinecone
• Experience with Whisper, Llama, Qwen, DeepSeek models

What we offer

• Fully remote working arrangement.
• Annual salary of $12,000–$16,000.
• Opportunity to work on cutting‑edge multimodal AI systems and open‑source model deployment.
• Technical leadership and mentoring responsibilities.