Lead the design and scaling of advanced AI systems transforming unstructured social media data into structured outputs. Develop multimodal pipelines integrating computer vision, speech recognition, and large language models while optimizing performance, cost, and data quality. Drive technical leadership, mentor junior engineers, and establish sustainable AI/ML infrastructure.
Key Highlights
Lead AI systems architecture for data-centric AI and multimodal workflows combining vision, speech, and text models
Optimize and scale AI pipelines using open-source models (Llama, Qwen) and high-throughput inference engines (vLLM, TGI)
Define technical roadmaps, mentor developers, and ensure scalable, high-quality data extraction at scale
Key Responsibilities
Design and implement multimodal AI pipelines combining computer vision, speech recognition, and large language models
Develop structured data extraction frameworks ensuring consistent, validated JSON outputs from generative models
Optimize model performance and reduce costs by transitioning from commercial APIs to fine-tuned open-source models
Implement data-centric AI techniques (Cleanlab, Snorkel) to automate large-scale labeling and improve dataset quality
Define architectural roadmaps, establish engineering standards, and mentor junior developers in AI/ML best practices
Support scalable data infrastructure for AI-driven enrichment workflows and retrieval systems
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Technical Skills Required
Python
Deep Learning Frameworks (PyTorch/TensorFlow)
Large Language Model Orchestration (DSPy, LangChain, LlamaIndex)
Benefits & Perks
Fully remote working arrangement
Annual salary of $120,000–$160,000
Technical leadership opportunities
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Nice to Have
Experience with social media data pipelines (TikTok, Instagram Reels, YouTube Shorts)
Background in data-centric AI, active learning, or synthetic data generation
Vector database expertise (Qdrant, pgvector, Pinecone) and RAG architectures
Job Description
This is an opportunity for an experienced AI engineer to design and scale advanced AI systems that transform unstructured social media content into high-quality, structured data products. You will lead the development of multimodal pipelines combining computer vision, speech recognition, and large language models. The role focuses on building reliable data extraction workflows, optimizing model performance, and improving the quality of large-scale datasets. You will also drive the adoption of open-source models and efficient inference infrastructure to improve scalability and control costs. Working at the intersection of applied AI, data engineering, and social media intelligence, you will help shape the technical architecture of an evolving AI and Data Lab. You will also provide technical guidance to junior developers and establish engineering practices that support sustainable growth.
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