Machine Learning Engineer (Video Understanding & Segmentation) @ Maxinsights Corporation

AI Startup

On-siteOn-siteFull-time$140k – $220k / year

About this role

Machine Learning Engineer (Video Understanding & Segmentation) @ Maxinsights Corporation - Back to Maxinsights Corporation’s Job Listings Machine Learning Engineer (Video Understanding & Segmentation) Location Santa Clara Employment Type Full time Location Type On-site Department Engineering Job Description: We are seeking a highly motivated Machine Learning Engineer to join our core research and development team, focused on video understanding and segmentation. In this role, you will build the systems that let us search, decompose, and describe massive volumes of egocentric and human-robot video at scale — turning raw, unstructured footage into structured, searchable, and richly annotated training data. You will work across video/image embedding models, LLM-based video understanding, and agentic pipelines that orchestrate multiple models into end-to-end workflows. This is a foundational role that directly shapes the data quality and scalability of our entire training data platform. Responsibilities Build and optimize video/image embedding pipelines using CLIP-style and other vision-language embedding models to power large-scale, multi-modal video search and retrieval. Develop LLM-based video understanding systems for semantic indexing, summarization, and question-answering over long-form egocentric and third-person video. Design and implement instruction-level and action-level video chunking/segmentation algorithms that decompose long videos into structured, temporally-aligned clips. Build automated video captioning systems that combine vision-language models and LLMs to produce fine-grained, temporally-grounded descriptions of actions and scenes. Architect agentic systems and orchestration pipelines that chain embedding, captioning, retrieval, and LLM reasoning steps into reliable, end-to-end video understanding workflows. Develop and scale video search infrastructure (vector indexing, retrieval, ranking) to support semantic an

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