Design and scale advanced multimodal AI systems to transform unstructured social media content into structured data products. Lead the development of pipelines integrating computer vision, speech recognition, and LLMs while optimizing model performance and cost. Requires 5+ years of experience in applied AI, Python, and production LLM orchestration with open-source model deployment.
Key Highlights
Lead the design of multimodal AI pipelines combining computer vision, speech-to-text, and large language models.
Transition workloads from commercial APIs to fine-tuned open-source models using high-throughput inference engines.
Establish engineering standards and mentor junior developers in building robust AI systems.
Key Responsibilities
Design and build automated ingestion pipelines combining computer vision, speech-to-text, and large language models.
Develop programmatic extraction frameworks to ensure generative models produce consistent, validated JSON outputs.
Transition workloads from commercial AI APIs to fine-tuned open-source models deployed through local or high-throughput inference engines.
Implement data-centric AI techniques and frameworks to automate large-scale labeling processes and improve dataset quality.
Define architectural roadmaps, establish engineering standards, and guide junior developers in building robust AI systems.
Support the development of AI-driven enrichment workflows and retrieval systems for processing large volumes of unstructured content.
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Technical Skills Required
Python
PyTorch
Large Language Models
Benefits & Perks
Fully remote working arrangement
Annual salary of $12,000–$16,000
Opportunity to work on advanced multimodal AI systems
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Nice to Have
Experience building social media data pipelines involving platforms such as TikTok, Instagram Reels, or YouTube Shorts.
Background in data-centric AI, active learning, or synthetic data generation.
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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