Lookup
https://fravix.aiAbout
Join Us in Building the Search Engine for Video đź”
At lookup, we believe the world's most valuable data asset is trapped. Video is everywhere, but it's unsearchable—a black box of insight that no one can open. We’re changing that. We're building the search engine for the visual world, so anyone can find a single moment in a mountain of footage, ask + analyse any video and autonomously take decisions from teaching our machines to watch a video.Â
Our Mission
To make video as accessible to machines as text and voice are today.
Text is queryable. Voice is transcribed. Video, the largest and richest data source of all, is still a black box. A computer can't understand it, and so its value remains trapped.
Our mission at lookup is to fix this.
When video is truly accessible to machines, it doesn't just mean a person can finally search their archives. It means an entirely new generation of automated workflows, creative tools, and intelligent applications can be built. We are not just building an app; we are building the API for software to see the world!
The lookup Engine: The Core Platform
At its core, lookup is a hardware-agnostic, API-first platform designed to do for unstructured video what a database does for structured data. Our proprietary platform ingests any video feed and transforms it into a rich, structured index. Every element—dialogue, on-screen text, objects, and actions—is cataloged, creating a queryable asset that allows users to ask complex questions about their visual content and receive answers in milliseconds.
Our Launch: "Ask Video Anything"
We published our "Ask Video Anything" engine. This public beta showcased our first-vision understanding, general-purpose model—a multi-modal AI optimized for the core tasks of Content Discovery and Visual Question Answering (VQA).
Tech stack
Python
Amazon Web Services (AWS)
Docker
PostgreSQL
RedisCandid answers by the company
At its core, lookup is a hardware-agnostic, API-first platform designed to do for unstructured video what a database does for structured data. Our proprietary platform ingests any video feed and transforms it into a rich, structured index. Every element—dialogue, on-screen text, objects, and actions—is cataloged, creating a queryable asset that allows users to ask complex questions about their visual content and receive answers in milliseconds.
Connect with the team
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Jobs at Lookup
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PythonPostgreSQLRedisAmazon Web Services (AWS)Our Mission
To make video as accessible to machines as text and voice are today.
At lookup, we believe the world's most valuable asset is trapped. Video is everywhere, but it's unsearchable—a black box of insight that no one can open or atleast open affordably. We’re changing that. We're building the search engine for the visual world, so anyone can find or do anything with video just by asking.
Text is queryable. Voice is transcribed. Video, the largest and richest data source of all, is still a black box. A computer can't understand it, and so its value remains trapped.
Our mission at lookup is to fix this.
About the Role
We are looking for founding Backend Engineers to build a highly performant, reliable, and scalable API platform that makes enterprise video knowledge readily available for video search, summarization, and natural‑language Q&A. You will partner closely with our ML team working on vision‑language models to productionize research and deliver fast, trustworthy APIs for customers.
Examples of technical challenges you will work on include: distributed video storage, a unified application framework and data model for indexing large video libraries, low‑latency clip retrieval, vector search at scale, and end‑to‑end build, test, deploy, and observability in cloud environments.
What You’ll Do:
- Design and build robust backend services and APIs (REST, gRPC) for vector search, video summarization, and video Q&A.
- Own API performance and reliability, including low‑latency retrieval, pagination, rate limiting, and backwards‑compatible versioning.
- Design schemas and tune queries in Postgres, and integrate with unstructured storage.
- Implement observability across metrics, logs, and traces. Set error budgets and SLOs.
- Write clear design docs and ship high‑quality, well‑tested code.
- Collaborate with ML engineers to integrate and productionize VLMs and retrieval pipelines.
- Take ownership of architecture from inception to production launch.
Who You Are:
- 3+ years of professional experience in backend development.
- Proven experience building and scaling polished WebSocket, gRPC, and REST APIs.
- Exposure to distributed systems and container orchestration (Docker and Kubernetes).
- Hands‑on experience with AWS.
- Strong knowledge of SQL (Postgres) and NoSQL (e.g., Cassandra), including schema design, query optimization, and scaling.
- Familiarity with our stack is a plus, but not mandatory: Python (FastAPI), Celery, Kafka, Postgres, Redis, Weaviate, React.
- Ability to diagnose complex issues, identify root causes, and implement effective fixes.
- Comfortable working in a fast‑paced startup environment.
Nice to have:
- Hands-on work with LLM agents, vector embeddings, or RAG applications.
- Building video streaming pipelines and storage systems at scale (FFmpeg, RTSP, WebRTC).
- Proficiency with modern frontend frameworks (React, TypeScript, Tailwind CSS) and responsive UI design.
Location & Culture
- Full-time, in-office role in Bangalore (we’re building fast and hands-on).
- Must be comfortable with a high-paced environment and collaboration across PST time zones for our US customers and investors.
- Expect startup speed — daily founder syncs, rapid design-to-prototype cycles, and a culture of deep ownership.
Why You’ll Love This Role
- Work on the frontier of video understanding and real-world AI — products that can redefine trust and automation.
- Build core APIs that make video queryable and power real customer use.
- Own systems end to end: performance, reliability, and developer experience.
- Work closely with founders and collaborate in person in Bangalore.
- Competitive salary with meaningful early equity.
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